no code implementations • ACL 2022 • Chen Zhao, Yu Su, Adam Pauls, Emmanouil Antonios Platanios
Text-to-SQL parsers map natural language questions to programs that are executable over tables to generate answers, and are typically evaluated on large-scale datasets like Spider (Yu et al., 2018).
no code implementations • ECCV 2020 • Xin Xiong, Haipeng Xiong, Ke Xian, Chen Zhao, Zhiguo Cao, Xin Li
Depth completion is a widely studied problem of predicting a dense depth map from a sparse set of measurements and a single RGB image.
1 code implementation • EMNLP 2021 • Chenglei Si, Chen Zhao, Jordan Boyd-Graber
We incorporate answers for two settings: evaluation with additional answers and model training with equivalent answers.
1 code implementation • EMNLP 2021 • Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
This paper investigates whether models can learn to find evidence from a large corpus, with only distant supervision from answer labels for model training, thereby generating no additional annotation cost.
no code implementations • 27 Apr 2024 • Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu
We empirically show that CausalDiffAE learns a disentangled latent space and is capable of generating high-quality counterfactual images.
no code implementations • 4 Apr 2024 • Dawit Mureja Argaw, Mattia Soldan, Alejandro Pardo, Chen Zhao, Fabian Caba Heilbron, Joon Son Chung, Bernard Ghanem
Movie trailers are an essential tool for promoting films and attracting audiences.
1 code implementation • 30 Mar 2024 • Guande Wu, Chen Zhao, Claudio Silva, He He
Language agents that interact with the world on their own have great potential for automating digital tasks.
no code implementations • 25 Mar 2024 • Qin Tian, Wenjun Wang, Chen Zhao, Minglai Shao, Wang Zhang, Dong Li
Traditional machine learning methods heavily rely on the independent and identically distribution assumption, which imposes limitations when the test distribution deviates from the training distribution.
no code implementations • 25 Mar 2024 • Bin Chen, Zhenyu Zhang, Weiqi Li, Chen Zhao, Jiwen Yu, Shijie Zhao, Jie Chen, Jian Zhang
To enable such memory-intensive end-to-end finetuning, we propose a novel two-level invertible design to transform both (1) the multi-step sampling process and (2) the noise estimation U-Net in each step into invertible networks.
no code implementations • 22 Mar 2024 • Jinbo Wu, Xing Liu, Chenming Wu, Xiaobo Gao, Jialun Liu, Xinqi Liu, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang
We propose an optimal viewpoint selection strategy, that finds the most miniature set of viewpoints covering all the faces of a mesh.
1 code implementation • 20 Mar 2024 • Chen Zhao, Tong Zhang, Zheng Dang, Mathieu Salzmann
Determining the relative pose of an object between two images is pivotal to the success of generalizable object pose estimation.
no code implementations • 15 Mar 2024 • Hao Li, Yuanyuan Gao, Chenming Wu, Dingwen Zhang, Yalun Dai, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang, Junwei Han
Specifically, we design a novel joint learning framework that consists of an Iterative Pose Optimization Network (IPO-Net) and a Generalizable 3D-Gaussians (G-3DG) model.
1 code implementation • 3 Mar 2024 • Chen Zhao, Chenyu Dong, Weiling Cai
PA-Diff consists of Physics Prior Generation (PPG) Branch, Implicit Neural Reconstruction (INR) Branch, and Physics-aware Diffusion Transformer (PDT) Branch.
no code implementations • 26 Feb 2024 • Xinqi Liu, Chenming Wu, Jialun Liu, Xing Liu, Jinbo Wu, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang
In this paper, we present a novel method that facilitates the creation of vivid 3D Gaussian avatars from monocular video inputs (GVA).
1 code implementation • 26 Feb 2024 • Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis
These representations are typically explicit, such as 3D point clouds or meshes, and thus provide information in the direct surroundings of the intermediate hand pose estimate.
Ranked #1 on hand-object pose on HO-3D (using extra training data)
no code implementations • 24 Feb 2024 • Chen Zhao, Zhihui Xu, Pukar Baral, Michel Esposito, Weihua Zhou
However, deep learning-based methods encounter challenges in generating semantic labels for arterial segments, primarily due to the morphological similarity between arterial branches.
no code implementations • 19 Feb 2024 • Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
Theoretical analysis yields sub-linear upper bounds for both loss regret and the cumulative violation of fairness constraints.
no code implementations • 19 Feb 2024 • Yanda Chen, Chen Zhao, Zhou Yu, Kathleen McKeown, He He
Pre-trained language models (LMs) are capable of in-context learning (ICL): they can adapt to a task with only a few examples given in the prompt without any parameter update.
no code implementations • 10 Feb 2024 • Shaojie Tang, Penpen Miao, Xingyu Gao, Yu Zhong, Dantong Zhu, Haixing Wen, Zhihui Xu, Qiuyue Wei, Hongping Yao, Xin Huang, Rui Gao, Chen Zhao, Weihua Zhou
Fourthly, we employed ICP, SICP or CPD algorithm to achieve a fine registration for the point clouds (together with the special points of APIGs) of the LV epicardial surfaces (LVERs) in SPECT and CTA images.
no code implementations • 4 Feb 2024 • Huan Huang, Liheng Qiu, Shenmiao Yang, Longxi Li, Jiaofen Nan, Yanting Li, Chuang Han, Fubao Zhu, Chen Zhao, Weihua Zhou
Methods: Our lymphoma segmentation approach combines a vision transformer with dual encoders, adeptly fusing PET and CT data via multimodal cross-attention fusion (MMCAF) module.
no code implementations • 2 Feb 2024 • Minglai Shao, Dong Li, Chen Zhao, Xintao Wu, Yujie Lin, Qin Tian
Supervised fairness-aware machine learning under distribution shifts is an emerging field that addresses the challenge of maintaining equitable and unbiased predictions when faced with changes in data distributions from source to target domains.
no code implementations • 18 Jan 2024 • Jinzhi Zheng, Libo Zhang, Yanjun Wu, Chen Zhao
Arbitrary shape scene text detection is of great importance in scene understanding tasks.
no code implementations • 18 Jan 2024 • Jinzhi Zheng, Libo Zhang, Yanjun Wu, Chen Zhao
Segmentation-based scene text detection algorithms can handle arbitrary shape scene texts and have strong robustness and adaptability, so it has attracted wide attention.
no code implementations • 18 Jan 2024 • Jinzhi Zheng, Ruyi Ji, Libo Zhang, Yanjun Wu, Chen Zhao
However, the guidance of visual cues is ignored in the process of semantic mining, which limits the performance of the algorithm in recognizing irregular scene text.
no code implementations • 16 Jan 2024 • Kaixin Huang, Li Shen, Chen Zhao, Chun Yuan, DaCheng Tao
We aim to investigate whether Decision Transformer (DT), another offline RL paradigm, can serve as a more suitable offline continuous learner to address these issues.
1 code implementation • 8 Jan 2024 • Chen Zhao, Shuming Liu, Karttikeya Mangalam, Guocheng Qian, Fatimah Zohra, Abdulmohsen Alghannam, Jitendra Malik, Bernard Ghanem
We use two coefficients on either type of residual connections respectively, and introduce a dynamic training strategy that seamlessly transitions the pretrained model to a reversible network with much higher numerical precision.
no code implementations • 8 Dec 2023 • Yahao Shi, Yanmin Wu, Chenming Wu, Xing Liu, Chen Zhao, Haocheng Feng, Jingtuo Liu, Liangjun Zhang, Jian Zhang, Bin Zhou, Errui Ding, Jingdong Wang
This paper presents GIR, a 3D Gaussian Inverse Rendering method for relightable scene factorization.
1 code implementation • 30 Nov 2023 • Kristen Grauman, Andrew Westbury, Lorenzo Torresani, Kris Kitani, Jitendra Malik, Triantafyllos Afouras, Kumar Ashutosh, Vijay Baiyya, Siddhant Bansal, Bikram Boote, Eugene Byrne, Zach Chavis, Joya Chen, Feng Cheng, Fu-Jen Chu, Sean Crane, Avijit Dasgupta, Jing Dong, Maria Escobar, Cristhian Forigua, Abrham Gebreselasie, Sanjay Haresh, Jing Huang, Md Mohaiminul Islam, Suyog Jain, Rawal Khirodkar, Devansh Kukreja, Kevin J Liang, Jia-Wei Liu, Sagnik Majumder, Yongsen Mao, Miguel Martin, Effrosyni Mavroudi, Tushar Nagarajan, Francesco Ragusa, Santhosh Kumar Ramakrishnan, Luigi Seminara, Arjun Somayazulu, Yale Song, Shan Su, Zihui Xue, Edward Zhang, Jinxu Zhang, Angela Castillo, Changan Chen, Xinzhu Fu, Ryosuke Furuta, Cristina Gonzalez, Prince Gupta, Jiabo Hu, Yifei HUANG, Yiming Huang, Weslie Khoo, Anush Kumar, Robert Kuo, Sach Lakhavani, Miao Liu, Mi Luo, Zhengyi Luo, Brighid Meredith, Austin Miller, Oluwatumininu Oguntola, Xiaqing Pan, Penny Peng, Shraman Pramanick, Merey Ramazanova, Fiona Ryan, Wei Shan, Kiran Somasundaram, Chenan Song, Audrey Southerland, Masatoshi Tateno, Huiyu Wang, Yuchen Wang, Takuma Yagi, Mingfei Yan, Xitong Yang, Zecheng Yu, Shengxin Cindy Zha, Chen Zhao, Ziwei Zhao, Zhifan Zhu, Jeff Zhuo, Pablo Arbelaez, Gedas Bertasius, David Crandall, Dima Damen, Jakob Engel, Giovanni Maria Farinella, Antonino Furnari, Bernard Ghanem, Judy Hoffman, C. V. Jawahar, Richard Newcombe, Hyun Soo Park, James M. Rehg, Yoichi Sato, Manolis Savva, Jianbo Shi, Mike Zheng Shou, Michael Wray
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge.
2 code implementations • 28 Nov 2023 • Shuming Liu, Chen-Lin Zhang, Chen Zhao, Bernard Ghanem
In this paper, we reduce the memory consumption for end-to-end training, and manage to scale up the TAD backbone to 1 billion parameters and the input video to 1, 536 frames, leading to significant detection performance.
Ranked #1 on Temporal Action Localization on EPIC-KITCHENS-100
1 code implementation • 28 Nov 2023 • Chen Zhao, Weiling Cai, Chenyu Dong, Chengwei Hu
Underwater images are subject to intricate and diverse degradation, inevitably affecting the effectiveness of underwater visual tasks.
no code implementations • 23 Nov 2023 • Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen
Achieving the generalization of an invariant classifier from source domains to shifted target domains while simultaneously considering model fairness is a substantial and complex challenge in machine learning.
1 code implementation • 16 Nov 2023 • Yilun Zhao, Hongjun Liu, Yitao Long, Rui Zhang, Chen Zhao, Arman Cohan
We introduce KnowledgeMath, a novel benchmark designed to evaluate LLMs' capabilities in applying financial knowledge to solve complex math word problems.
no code implementations • 1 Nov 2023 • Ni Yao, Hang Hu, Kaicong Chen, Chen Zhao, Yuan Guo, Boya Li, Jiaofen Nan, Yanting Li, Chuang Han, Fubao Zhu, Weihua Zhou, Li Tian
By using five-fold cross-validation, a deep learning model incorporating uncertainty estimation was developed to classify RCC subtypes into clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC).
no code implementations • 22 Oct 2023 • Vaibhav Mavi, Abulhair Saparov, Chen Zhao
Applying existing question answering (QA) systems to specialized domains like law and finance presents challenges that necessitate domain expertise.
no code implementations • 19 Oct 2023 • Chenglei Si, Navita Goyal, Sherry Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daumé III, Jordan Boyd-Graber
To reduce over-reliance on LLMs, we ask LLMs to provide contrastive information - explain both why the claim is true and false, and then we present both sides of the explanation to users.
no code implementations • 12 Oct 2023 • Chen Zhao, Kuan-Jui Su, Chong Wu, Xuewei Cao, Qiuying Sha, Wu Li, Zhe Luo, Tian Qin, Chuan Qiu, Lan Juan Zhao, Anqi Liu, Lindong Jiang, Xiao Zhang, Hui Shen, Weihua Zhou, Hong-Wen Deng
By learning the latent representations of both omics data, our method can effectively impute missing metabolomics values based on genomic information.
no code implementations • 5 Oct 2023 • Chen Zhao, Tong Zhang, Mathieu Salzmann
Our goal then is to estimate the relative object pose between this reference view and a query image that depicts the object in a different pose.
no code implementations • 22 Sep 2023 • Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen
This approach effectively separates environmental information and sensitive attributes from the embedded representation of classification features.
no code implementations • 18 Sep 2023 • Haoliang Wang, Chen Zhao, Yunhui Guo, Kai Jiang, Feng Chen
In this study, we introduce a novel problem, semantic OOD detection across domains, which simultaneously addresses both distributional shifts.
1 code implementation • 15 Sep 2023 • Kristoffer Larsen, Chen Zhao, Joyce Keyak, Qiuying Sha, Diana Paez, Xinwei Zhang, Guang-Uei Hung, Jiangang Zou, Amalia Peix, Weihua Zhou
Uncertainty quantification from Ensemble 1 allowed for multi-stage decision-making to determine if the acquisition of SPECT data for a patient is necessary.
1 code implementation • 8 Sep 2023 • Chen Zhao, Weiling Cai, Chenyu Dong, Ziqi Zeng
Underwater images suffer from complex and diverse degradation, which inevitably affects the performance of underwater visual tasks.
no code implementations • 31 Aug 2023 • Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao
As the basic element of graph-structured data, node has been recognized as the main object of study in graph representation learning.
no code implementations • 31 Aug 2023 • Yuxuan Hu, Jing Zhang, Zhe Zhao, Chen Zhao, Xiaodong Chen, Cuiping Li, Hong Chen
Structured pruning is a widely used technique for reducing the size of pre-trained language models (PLMs), but current methods often overlook the potential of compressing the hidden dimension (d) in PLMs, a dimension critical to model size and efficiency.
no code implementations • 31 Aug 2023 • Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen
In aligning p with p*, several factors can affect the adaptation rate, including the causal dependencies between variables in p. In real-life scenarios, however, we have to consider the fairness of the training process, and it is particularly crucial to involve a sensitive variable (bias) present between a cause and an effect variable.
no code implementations • 20 Aug 2023 • Chen Zhao, Michele Esposito, Zhihui Xu, Weihua Zhou
Coronary artery disease (CAD) is one of the primary causes leading to death worldwide.
no code implementations • 30 Jul 2023 • Jinbo Wu, Xiaobo Gao, Xing Liu, Zhengyang Shen, Chen Zhao, Haocheng Feng, Jingtuo Liu, Errui Ding
In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models.
no code implementations • 17 Jul 2023 • Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen McKeown
To answer these questions, we propose to evaluate $\textbf{counterfactual simulatability}$ of natural language explanations: whether an explanation can enable humans to precisely infer the model's outputs on diverse counterfactuals of the explained input.
1 code implementation • 25 Jun 2023 • Yilun Zhao, Chen Zhao, Linyong Nan, Zhenting Qi, Wenlin Zhang, Xiangru Tang, Boyu Mi, Dragomir Radev
Despite significant progress having been made in question answering on tabular data (Table QA), it's unclear whether, and to what extent existing Table QA models are robust to task-specific perturbations, e. g., replacing key question entities or shuffling table columns.
no code implementations • 31 May 2023 • Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen
To this end, in this paper, we propose a novel algorithm under the assumption that data collected at each time can be disentangled with two representations, an environment-invariant semantic factor and an environment-specific variation factor.
no code implementations • 28 May 2023 • Lama Alssum, Juan Leon Alcazar, Merey Ramazanova, Chen Zhao, Bernard Ghanem
Studying continual learning in the video domain poses even more challenges, as video data contains a large number of frames, which places a higher burden on the replay memory.
no code implementations • 24 May 2023 • Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan Boyd-Graber
Beyond generalizability, the interpretable design of MoRE improves selective question answering results compared to baselines without incorporating inter-expert agreement.
no code implementations • 23 May 2023 • Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho
Large language models (LLMs) have achieved widespread success on a variety of in-context few-shot tasks, but this success is typically evaluated via correctness rather than consistency.
no code implementations • 21 May 2023 • Chen Zhao, Zhihui Xu, Guang-Uei Hung, Weihua Zhou
The presence of atherosclerotic lesions in coronary arteries is the underlying pathophysiological basis of CAD, and accurate extraction of individual arterial branches using invasive coronary angiography (ICA) is crucial for stenosis detection and CAD diagnosis.
no code implementations • 4 May 2023 • Kristoffer Larsena, Zhuo He, Chen Zhao, Xinwei Zhang, Quiying Sha, Claudio T Mesquitad, Diana Paeze, Ernest V. Garciaf, Jiangang Zou, Amalia Peix, Weihua Zhou
The DL model outperformed the ML models, showcasing the additional predictive benefit of utilizing SPECT MPI polarmaps.
1 code implementation • CVPR 2023 • Chong Mou, Youmin Xu, Jiechong Song, Chen Zhao, Bernard Ghanem, Jian Zhang
For large-capacity, we present a reversible pipeline to perform multiple videos hiding and recovering through a single invertible neural network (INN).
no code implementations • 24 Apr 2023 • Chen Zhao, Wei-Ling Cai, Zheng Yuan, Cheng-Wei Hu
Recently, unsupervised image-to-image translation methods based on contrastive learning have achieved state-of-the-art results in many tasks.
1 code implementation • 22 Apr 2023 • Chen Zhao, Wei-Ling Cai, Zheng Yuan
Similarly, we design a style contrastive loss to improve the global texture information of the generated images.
no code implementations • 12 Apr 2023 • Chen Zhao, Anqi Liu, Xiao Zhang, Xuewei Cao, Zhengming Ding, Qiuying Sha, Hui Shen, Hong-Wen Deng, Weihua Zhou
Integration of heterogeneous and high-dimensional multi-omics data is becoming increasingly important in understanding genetic data.
1 code implementation • ICCV 2023 • Jiwen Yu, Yinhuai Wang, Chen Zhao, Bernard Ghanem, Jian Zhang
In this work, we propose a training-Free conditional Diffusion Model (FreeDoM) used for various conditions.
1 code implementation • ICCV 2023 • Qiankun Gao, Chen Zhao, Yifan Sun, Teng Xi, Gang Zhang, Bernard Ghanem, Jian Zhang
1) Learning: the pre-trained model adapts to the new task by tuning an online PET module, along with our adaptation speed calibration to align different PET modules, 2) Accumulation: the task-specific knowledge learned by the online PET module is accumulated into an offline PET module through momentum update, 3) Ensemble: During inference, we respectively construct two experts with online/offline PET modules (which are favored by the novel/historical tasks) for prediction ensemble.
no code implementations • CVPR 2023 • Chen Zhao, Dawei Du, Anthony Hoogs, Christopher Funk
Existing methods for open-set action recognition focus on novelty detection that assumes video clips show a single action, which is unrealistic in the real world.
no code implementations • 29 Jan 2023 • Ni Yao, Yanhui Tian, Daniel Gama das Neves, Chen Zhao, Claudio Tinoco Mesquita, Wolney de Andrade Martins, Alair Augusto Sarmet Moreira Damas dos Santos, Yanting Li, Chuang Han, Fubao Zhu, Neng Dai, Weihua Zhou
For severity detection, the hybrid model with radiomics features of both lungs and EAT showed improvements in AUC, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) compared to the model with only lung radiomics features.
no code implementations • 20 Jan 2023 • Feng Mi, Chen Zhao, Zhuoyi Wang, Sadaf MD Halim, Xiaodi Li, Zhouxiang Wu, Latifur Khan, Bhavani Thuraisingham
With the increase of the adoption of blockchain technology in providing decentralized solutions to various problems, smart contracts have become more popular to the point that billions of US Dollars are currently exchanged every day through such technology.
no code implementations • 11 Jan 2023 • Chen Zhao, Zhihui Xu, Jingfeng Jiang, Michele Esposito, Drew Pienta, Guang-Uei Hung, Weihua Zhou
Semantic labeling of coronary arterial segments in invasive coronary angiography (ICA) is important for automated assessment and report generation of coronary artery stenosis in the computer-aided diagnosis of coronary artery disease (CAD).
no code implementations • CVPR 2023 • Chen Zhao, Shuming Liu, Karttikeya Mangalam, Bernard Ghanem
Temporal action localization (TAL) requires long-form reasoning to predict actions of various durations and complex content.
no code implementations • 23 Dec 2022 • Dennis Melamed, Cameron Johnson, Chen Zhao, Russell Blue, Philip Morrone, Anthony Hoogs, Brian Clipp
This new challenge involves a new dataset and metrics indicating solution performance when damage is more local and limited than in xBD.
1 code implementation • ICCV 2023 • Jinjie Mai, Abdullah Hamdi, Silvio Giancola, Chen Zhao, Bernard Ghanem
Yet, we point out that the low number of camera poses caused by camera re-localization from previous VQ3D methods severally hinders their overall success rate.
no code implementations • 29 Nov 2022 • Chen Zhao, Yinlin Hu, Mathieu Salzmann
The prior can be used to initialize the 3D object translation and facilitate 3D object rotation estimation.
1 code implementation • 25 Nov 2022 • Chen Zhao, Shuming Liu, Karttikeya Mangalam, Bernard Ghanem
Temporal action localization (TAL) requires long-form reasoning to predict actions of various durations and complex content.
no code implementations • 23 Nov 2022 • Sina Honari, Chen Zhao, Mathieu Salzmann, Pascal Fua
Analyzing and training 3D body posture models depend heavily on the availability of joint labels that are commonly acquired through laborious manual annotation of body joints or via marker-based joint localization using carefully curated markers and capturing systems.
no code implementations • 18 Nov 2022 • Jinjie Mai, Chen Zhao, Abdullah Hamdi, Silvio Giancola, Bernard Ghanem
Visual queries 3D localization (VQ3D) is a task in the Ego4D Episodic Memory Benchmark.
7 code implementations • 5 Oct 2022 • Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
no code implementations • 3 Oct 2022 • Chen Zhao, Joyce H Keyak, Xuewei Cao, Qiuying Sha, Li Wu, Zhe Luo, LanJuan Zhao, Qing Tian, Chuan Qiu, Ray Su, Hui Shen, Hong-Wen Deng, Weihua Zhou
The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion.
no code implementations • 3 Oct 2022 • Xuewei Cao, Joyce H Keyak, Sigurdur Sigurdsson, Chen Zhao, Weihua Zhou, Anqi Liu, Thomas Lang, Hong-Wen Deng, Vilmundur Gudnason, Qiuying Sha
The results showed that the average of the area under the receive operating characteristic curve (AUC) using PC1 was always higher than that using all FE parameters combined in the male subjects.
no code implementations • 27 Sep 2022 • Chen Zhao, Kai Xing Huang, Chun Yuan
Previous conservative estimation methods are usually difficult to avoid the impact of OOD actions on Q-value estimates.
1 code implementation • 16 Sep 2022 • Yanda Chen, Chen Zhao, Zhou Yu, Kathleen McKeown, He He
In-context learning (ICL) suffers from oversensitivity to the prompt, making it unreliable in real-world scenarios.
no code implementations • 7 Aug 2022 • Fubao Zhu, Guojie Wang, Chen Zhao, Saurabh Malhotra, Min Zhao, Zhuo He, Jianzhou Shi, Zhixin Jiang, Weihua Zhou
Five-fold cross-validation with 180 stress and 201 rest MPIs was used for training and internal validation; the remaining images were used for testing.
no code implementations • 24 Jun 2022 • Yinghui Meng, Zhenglong Du, Chen Zhao, Minghao Dong, Drew Pienta, Zhihui Xu, Weihua Zhou
A deep learning model U-Net 3+, which incorporates the full-scale skip connections and deep supervisions, was proposed for automatic extraction of coronary arteries from ICAs.
no code implementations • 7 Jun 2022 • Fubao Zhu, Jinyu Zhao, Chen Zhao, Shaojie Tang, Jiaofen Nan, Yanting Li, Zhongqiang Zhao, Jianzhou Shi, Zenghong Chen, Zhixin Jiang, Weihua Zhou
Conclusion: Our proposed method achieved a high accuracy in extracting LV myocardial contours and assessing LV function.
1 code implementation • 25 May 2022 • Chenglei Si, Chen Zhao, Sewon Min, Jordan Boyd-Graber
Building on those observations, we propose a new calibration metric, MacroCE, that better captures whether the model assigns low confidence to wrong predictions and high confidence to correct predictions.
no code implementations • 20 May 2022 • Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
Furthermore, to determine a good model parameter at each round, we propose a novel adaptive fairness-aware online meta-learning algorithm, namely FairSAOML, which is able to adapt to changing environments in both bias control and model precision.
1 code implementation • 14 May 2022 • Shuming Liu, Mengmeng Xu, Chen Zhao, Xu Zhao, Bernard Ghanem
We propose to sequentially forward the snippet frame through the video encoder, and backward only a small necessary portion of gradients to update the encoder.
1 code implementation • 11 Apr 2022 • Guocheng Qian, Xuanyang Zhang, Guohao Li, Chen Zhao, Yukang Chen, Xiangyu Zhang, Bernard Ghanem, Jian Sun
TNAS performs a modified bi-level Breadth-First Search in the proposed trees to discover a high-performance architecture.
1 code implementation • 27 Mar 2022 • Juan Leon Alcazar, Moritz Cordes, Chen Zhao, Bernard Ghanem
Recent advances in the Active Speaker Detection (ASD) problem build upon a two-stage process: feature extraction and spatio-temporal context aggregation.
Ranked #4 on Audio-Visual Active Speaker Detection on AVA-ActiveSpeaker (using extra training data)
1 code implementation • 24 Mar 2022 • Qiankun Gao, Chen Zhao, Bernard Ghanem, Jian Zhang
After RRL, the classification head is refined with global class-balanced classification loss to address the data imbalance issue as well as learn the decision boundaries between new and previous classes.
no code implementations • 19 Mar 2022 • Haocheng Yuan, Chen Zhao, Shichao Fan, Jiaxi Jiang, Jiaqi Yang
To the best of our knowledge, the proposed method is the first to mine 3D semantic consistent keypoints from a mutual reconstruction view.
no code implementations • 16 Mar 2022 • Chen Zhao, Yinlin Hu, Mathieu Salzmann
In this paper, we tackle the task of estimating the 3D orientation of previously-unseen objects from monocular images.
no code implementations • 3 Mar 2022 • Chen Zhao, Merey Ramazanova, Mengmeng Xu, Bernard Ghanem
To address these issues and precisely model temporal action detection, we formulate the task of temporal action detection in a novel perspective of semantic segmentation.
1 code implementation • 1 Mar 2022 • Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen
During the forward pass of Deep Neural Networks (DNNs), inputs gradually transformed from low-level features to high-level conceptual labels.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
no code implementations • 10 Feb 2022 • Merey Ramazanova, Victor Escorcia, Fabian Caba Heilbron, Chen Zhao, Bernard Ghanem
We validate our approach in two large-scale datasets, EPIC-Kitchens, and HOMAGE.
1 code implementation • CVPR 2022 • Mattia Soldan, Alejandro Pardo, Juan León Alcázar, Fabian Caba Heilbron, Chen Zhao, Silvio Giancola, Bernard Ghanem
The recent and increasing interest in video-language research has driven the development of large-scale datasets that enable data-intensive machine learning techniques.
Ranked #2 on Natural Language Moment Retrieval on MAD
7 code implementations • CVPR 2022 • Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei HUANG, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Ziwei Zhao, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fuegen, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite.
1 code implementation • 11 Oct 2021 • Chen Zhao, Shi Shi, Zhuo He, Cheng Wang, Zhongqiang Zhao, Xinli Li, Yanli Zhou, Weihua Zhou
By integrating the spatial features from each cardiac frame of the gated MPS and the temporal features from the sequential cardiac frames of the gated MPS, we developed a Spatial-Temporal V-Net (ST-VNet) for automatic extraction of RV endocardial and epicardial contours.
1 code implementation • 10 Oct 2021 • Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
Open-domain question answering answers a question based on evidence retrieved from a large corpus.
no code implementations • 6 Oct 2021 • Yinghui Meng, Minghao Dong, Xumin Dai, Haipeng Tang, Chen Zhao, Jingfeng Jiang, Shun Xu, Ying Zhou, Fubao Zhu1, Zhihui Xu, Weihua Zhou
More specifically, a detection algorithm is first used to detect the key points of coronary arteries, and then an optical flow method is employed to track the trajectories of the selected key points.
1 code implementation • 11 Sep 2021 • Chenglei Si, Chen Zhao, Jordan Boyd-Graber
We incorporate answers for two settings: evaluation with additional answers and model training with equivalent answers.
no code implementations • 21 Aug 2021 • Chen Zhao, Feng Chen, Bhavani Thuraisingham
To overcome such issues and bridge the gap, in this paper for the first time we proposed a novel online meta-learning algorithm, namely FFML, which is under the setting of unfairness prevention.
no code implementations • 1 Jun 2021 • Zhuo He, Xinwei Zhang, Chen Zhao, Zhiyong Qian, Yao Wang, Xiaofeng Hou, Jiangang Zou, Weihua Zhou
Correlation analysis was used to explain the relationships between new parameters with conventional LVMD parameters.
no code implementations • 25 Apr 2021 • Chen Zhao, Zhipeng Gao, Qian Wang, Kaile Xiao, Zijia Mo, M. Jamal Deen
With the proliferation of edge smart devices and the Internet of Vehicles (IoV) technologies, intelligent fatigue detection has become one of the most-used methods in our daily driving.
1 code implementation • NAACL 2021 • Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
Complex question answering often requires finding a reasoning chain that consists of multiple evidence pieces.
no code implementations • 23 Mar 2021 • Chen Zhao, Chenyan Xiong, Xin Qian, Jordan Boyd-Graber
DELFT's advantage comes from both the high coverage of its free-text knowledge graph-more than double that of dbpedia relations-and the novel graph neural network which reasons on the rich but noisy free-text evidence.
no code implementations • 21 Feb 2021 • Fubao Zhu, Zhengyuan Gao, Chen Zhao, Hanlei Zhu, Yong Dong, Jingfeng Jiang, Neng Dai, Weihua Zhou
In this paper, we aim to develop a deep learning-based method using an encoder-decoder deep architecture to automatically extract both lumen and MA border.
no code implementations • 3 Feb 2021 • Yu Deng, Ling Wang, Chen Zhao, Shaojie Tang, Xiaoguang Cheng, Hong-Wen Deng, Weihua Zhou
In this study, we proposed an approach based on deep learning for the automatic extraction of the periosteal and endosteal contours of proximal femur in order to differentiate cortical and trabecular bone compartments.
no code implementations • 3 Feb 2021 • Chen Zhao, Xiao-Shan Gao
In this paper, we propose a general scheme to analyze the gradient vanishing phenomenon, also known as the barren plateau phenomenon, in training quantum neural networks with the ZX-calculus.
no code implementations • 25 Jan 2021 • Chen Zhao, Haipeng Tang, Daniel McGonigle, Zhuo He, Chaoyang Zhang, Yu-Ping Wang, Hong-Wen Deng, Robert Bober, Weihua Zhou
We aim to develop an automatic algorithm by deep learning to extract coronary arteries from ICAs. In this study, a multi-input and multi-scale (MIMS) U-Net with a two-stage recurrent training strategy was proposed for the automatic vessel segmentation.
1 code implementation • ICCV 2021 • Chen Zhao, Yixiao Ge, Feng Zhu, Rui Zhao, Hongsheng Li, Mathieu Salzmann
Correspondence selection aims to correctly select the consistent matches (inliers) from an initial set of putative correspondences.
no code implementations • 3 Dec 2020 • Tian Yu, Qicheng Sun, Chen Zhao, Jiajia Zhou, Masao Doi
When a capillary channel with corners is wetted by a fluid, there are regions where the fluid fills the whole cross-section and regions where only the corners are filled by the fluid.
Soft Condensed Matter
1 code implementation • ICCV 2021 • Chen Zhao, Ali Thabet, Bernard Ghanem
We have two key components in VSGN: video self-stitching (VSS) and cross-scale graph pyramid network (xGPN).
Ranked #16 on Temporal Action Localization on ActivityNet-1.3
no code implementations • 13 Nov 2020 • KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Rishabh Iyer, Feng Chen
Model-Agnostic Meta-Learning (MAML), a popular gradient-based meta-learning framework, assumes that the contribution of each task or instance to the meta-learner is equal.
2 code implementations • Findings of the Association for Computational Linguistics 2020 • Tianze Shi, Chen Zhao, Jordan Boyd-Graber, Hal Daumé III, Lillian Lee
Large-scale semantic parsing datasets annotated with logical forms have enabled major advances in supervised approaches.
1 code implementation • 26 Sep 2020 • Chen Zhao, Feng Chen, Zhuoyi Wang, Latifur Khan
In this work, we propose a Primal-Dual Fair Meta-learning framework, namely PDFM, which learns to train fair machine learning models using only a few examples based on data from related tasks.
no code implementations • 23 Sep 2020 • Chen Zhao, Changbin Li, Jincheng Li, Feng Chen
Artificial intelligence nowadays plays an increasingly prominent role in our life since decisions that were once made by humans are now delegated to automated systems.
no code implementations • 23 Sep 2020 • Chen Zhao, Feng Chen
In this work, we develop a novel fairness learning approach for multi-task regression models based on a biased training dataset, using a popular rank-based non-parametric independence test, i. e., Mann Whitney U statistic, for measuring the dependency between target variable and protected variables.
no code implementations • 23 Sep 2020 • Chen Zhao, Feng Chen
In this work, we first discover discrimination from data using a causal Bayesian knowledge graph which not only demonstrates the dependency of the protected variable on target but also indicates causal effects between all variables.
no code implementations • 20 Jun 2020 • Xuan Hua, Jungang Han, Chen Zhao, Haipeng Tang, Zhuo He, Jinshan Tang, Qing-Hui Chen, Shaojie Tang, Weihua Zhou
This paper presents an end-to-end ECG signal classification method based on a novel segmentation strategy via 1D Convolutional Neural Networks (CNN) to aid the classification of ECG signals.
no code implementations • 9 Jun 2020 • Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Shreyasee Amin, Elizabeth J. Atkinson, Lan-Juan Zhao, Michael J. Serou, Chaoyang Zhang, Hui Shen, Hong-Wen Deng, Weihua Zhou
During the experiments for the entire cohort then for male and female subjects separately, 90% of the subjects were used in 10-fold cross-validation for training and internal validation, and to select the optimal parameters of the proposed models; the rest of the subjects were used to evaluate the performance of models.
1 code implementation • ICLR 2020 • Chen Zhao, Chenyan Xiong, Corby Rosset, Xia Song, Paul Bennett, Saurabh Tiwary
Transformers have achieved new heights modeling natural language as a sequence of text tokens.
Ranked #42 on Question Answering on HotpotQA
1 code implementation • 29 Dec 2019 • Chen Zhao, Xiao-Shan Gao
In this paper, we introduce a quantum extension of classical DNN, QDNN.
no code implementations • ECCV 2020 • Ruyi Ji, Dawei Du, Libo Zhang, Longyin Wen, Yanjun Wu, Chen Zhao, Feiyue Huang, Siwei Lyu
In this paper, we design a novel semantic neural tree for human parsing, which uses a tree architecture to encode physiological structure of human body, and designs a coarse to fine process in a cascade manner to generate accurate results.
7 code implementations • CVPR 2020 • Mengmeng Xu, Chen Zhao, David S. Rojas, Ali Thabet, Bernard Ghanem
In this work, we propose a graph convolutional network (GCN) model to adaptively incorporate multi-level semantic context into video features and cast temporal action detection as a sub-graph localization problem.
Ranked #5 on Temporal Action Localization on EPIC-KITCHENS-100
1 code implementation • 1 Nov 2019 • Chen Zhao, Jiaqi Yang, Xin Xiong, Angfan Zhu, Zhiguo Cao, Xin Li
To the best of our knowledge, this work is the first principled approach toward adaptively combining global and local information under the context of RI point cloud analysis.
2 code implementations • CVPR 2020 • Ruyi Ji, Longyin Wen, Libo Zhang, Dawei Du, Yanjun Wu, Chen Zhao, Xianglong Liu, Feiyue Huang
Specifically, we incorporate convolutional operations along edges of the tree structure, and use the routing functions in each node to determine the root-to-leaf computational paths within the tree.
Ranked #33 on Fine-Grained Image Classification on Stanford Cars
Fine-Grained Image Classification Fine-Grained Visual Categorization
no code implementations • 3 Sep 2019 • Chen Zhao, Jiaqi Yang, Ke Xian, Zhiguo Cao, Xin Li
Matching corresponding features between two images is a fundamental task to computer vision with numerous applications in object recognition, robotics, and 3D reconstruction.
1 code implementation • 30 Apr 2019 • Chen Zhao, Jiaqi Yang, Yang Xiao, Zhiguo Cao
Correspondence selection aiming at seeking correct feature correspondences from raw feature matches is pivotal for a number of feature-matching-based tasks.
no code implementations • 27 Apr 2019 • Jiaqi Yang, Chen Zhao, Ke Xian, Angfan Zhu, Zhiguo Cao
This paper presents a simple yet very effective data-driven approach to fuse both low-level and high-level local geometric features for 3D rigid data matching.
no code implementations • 10 Apr 2019 • Chen Zhao, Bernard Ghanem
Although deep convolutional neural networks (CNNs) have achieved great success in computer vision tasks, its real-world application is still impeded by its voracious demand of computational resources.
1 code implementation • CVPR 2019 • Chen Zhao, Zhiguo Cao, Chi Li, Xin Li, Jiaqi Yang
Feature correspondence selection is pivotal to many feature-matching based tasks in computer vision.
no code implementations • EMNLP 2018 • Ahmed Elgohary, Chen Zhao, Jordan Boyd-Graber
Previous work on question-answering systems mainly focuses on answering individual questions, assuming they are independent and devoid of context.
1 code implementation • 9 May 2016 • Chengxi Ye, Chen Zhao, Yezhou Yang, Cornelia Fermuller, Yiannis Aloimonos
LightNet is a lightweight, versatile and purely Matlab-based deep learning framework.
no code implementations • LREC 2016 • Takakazu Imada, Yusuke Inoue, Lei Chen, Syunya Doi, Tian Nie, Chen Zhao, Takehito Utsuro, Yasuhide Kawada
We finally propose how to predict the market share of a specific product genre based on the rates of concerns of those who search for Web pages.
no code implementations • 30 Apr 2014 • Jian Zhang, Chen Zhao, Debin Zhao, Wen Gao
From many fewer acquired measurements than suggested by the Nyquist sampling theory, compressive sensing (CS) theory demonstrates that, a signal can be reconstructed with high probability when it exhibits sparsity in some domain.