1 code implementation • ECCV 2020 • Ziyi Meng, Jiawei Ma, Xin Yuan
Coded aperture snapshot spectral imaging (CASSI) is an effective tool to capture real-world 3D hyperspectral images.
Ranked #7 on Spectral Reconstruction on Real HSI
1 code implementation • ECCV 2020 • Ziheng Cheng, Ruiying Lu, Zhengjue Wang, Hao Zhang, Bo Chen, Ziyi Meng, Xin Yuan
This measurement and the modulation masks are fed into our Recurrent Neural Network (RNN) to reconstruct the desired high-speed frames.
1 code implementation • 23 Apr 2024 • Kai Li, Xin Yuan, Jingjing Zheng, Wei Ni, Falko Dressler, Abbas Jamalipour
This paper puts forth a new training data-untethered model poisoning (MP) attack on federated learning (FL).
1 code implementation • ICCV 2023 • Ping Wang, Lishun Wang, Xin Yuan
We believe this is a milestone for real-world video SCI.
1 code implementation • 7 Apr 2024 • Gang Qu, Ping Wang, Xin Yuan
In this paper, we propose a deep unfolding network with hybrid-attention Transformer on Kronecker SPI model, dubbed HATNet, to improve the imaging quality of real SPI cameras.
1 code implementation • 29 Mar 2024 • Yunhao Li, Xiaodong Wang, Ping Wang, Xin Yuan, Peidong Liu
SCI is a cost-effective method that enables the recording of high-dimensional data, such as hyperspectral or temporal information, into a single image using low-cost 2D imaging sensors.
1 code implementation • 29 Mar 2024 • Gengchen Zhang, Yulun Zhang, Xin Yuan, Ying Fu
For the second issue, we present a distribution-aware binary convolution, which captures the distribution characteristics of real-valued input and incorporates them into plain binary convolutions to alleviate the degradation in performance.
no code implementations • 23 Feb 2024 • Zejun Zhang, Li Zhang, Xin Yuan, Anlan Zhang, Mengwei Xu, Feng Qian
With the advancement of Large Language Models (LLMs), increasingly sophisticated and powerful GPTs are entering the market.
no code implementations • 6 Feb 2024 • Siguo Bi, Xin Yuan, Shuyan Hu, Kai Li, Wei Ni, Ekram Hossain, Xin Wang
The advent of communication technologies marks a transformative phase in critical infrastructure construction, where the meticulous analysis of failures becomes paramount in achieving the fundamental objectives of continuity, security, and availability.
no code implementations • 18 Jan 2024 • Xin Yuan, Jinoo Baek, Keyang Xu, Omer Tov, Hongliang Fei
We propose an efficient diffusion-based text-to-video super-resolution (SR) tuning approach that leverages the readily learned capacity of pixel level image diffusion model to capture spatial information for video generation.
no code implementations • 10 Jan 2024 • JianQiao Sun, Yudi Su, Hao Zhang, Ziheng Cheng, Zequn Zeng, Zhengjue Wang, Bo Chen, Xin Yuan
To address these problems, in this paper, we propose a novel VC pipeline to generate captions directly from the compressed measurement, which can be captured by a snapshot compressive sensing camera and we dub our model SnapCap.
no code implementations • 27 Dec 2023 • Xin Yuan, Ning li, Kang Wei, Wenchao Xu, Quan Chen, Hao Chen, Song Guo
The model segmentation without user mobility has been investigated deeply by previous works.
no code implementations • 27 Dec 2023 • Lixiang Xu, Qingzhe Cui, Richang Hong, Wei Xu, Enhong Chen, Xin Yuan, Chenglong Li, Yuanyan Tang
The large model GMViT achieves excellent 3D classification and retrieval results on the benchmark datasets ModelNet, ShapeNetCore55, and MCB.
no code implementations • 26 Dec 2023 • Xin Yuan, Ning li, Tuo Zhang, Muqing Li, YuWen Chen, Jose Fernan Martinez Ortega, Song Guo
Specifically, when the mobile user has a large model inference task needed to be calculated in the NOMA-based MEC, it will take the energy consumption of both device and edge server and the inference latency into account to find the optimal model split strategy, subchannel allocation strategy (uplink and downlink), and transmission power allocation strategy (uplink and downlink).
no code implementations • 30 Nov 2023 • Kai Li, Jingjing Zheng, Xin Yuan, Wei Ni, Ozgur B. Akan, H. Vincent Poor
The attacker then adversarially regenerates the graph structural correlations while maximizing the FL training loss, and subsequently generates malicious local models using the adversarial graph structure and the training data features of the benign ones.
no code implementations • 25 Nov 2023 • Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang, Ekram Hossain, H. Vincent Poor
Federated learning (FL) can suffer from a communication bottleneck when deployed in mobile networks, limiting participating clients and deterring FL convergence.
no code implementations • 24 Nov 2023 • Zongliang Wu, Ruiying Lu, Ying Fu, Xin Yuan
Snapshot compressive spectral imaging reconstruction aims to reconstruct three-dimensional spatial-spectral images from a single-shot two-dimensional compressed measurement.
1 code implementation • 24 Nov 2023 • Zheng Chen, Yulun Zhang, Jinjin Gu, Xin Yuan, Linghe Kong, Guihai Chen, Xiaokang Yang
Specifically, we first design a text-image generation pipeline to integrate text into the SR dataset through the text degradation representation and degradation model.
1 code implementation • 24 Nov 2023 • Zhiteng Li, Yulun Zhang, Jing Lin, Haotong Qin, Jinjin Gu, Xin Yuan, Linghe Kong, Xiaokang Yang
In this work, we propose a Binarized Dual Residual Network (BiDRN), a novel quantization method to estimate the 3D human body, face, and hands parameters efficiently.
no code implementations • 23 Nov 2023 • Cyrus Zhou, Pedro Savarese, Vaughn Richard, Zack Hassman, Xin Yuan, Michael Maire, Michael DiBrino, Yanjing Li
We present an end-to-end co-design approach encompassing computer architecture, training algorithm, and inference optimization to efficiently execute networks with fine-grained heterogeneous precisions.
no code implementations • 3 Nov 2023 • Xin Yuan, Jie Guo, Weidong Qiu, Zheng Huang, Shujun Li
Mis- and disinformation online have become a major societal problem as major sources of online harms of different kinds.
no code implementations • 27 Sep 2023 • Xin Yuan, Michael Maire
We develop a neural network architecture which, trained in an unsupervised manner as a denoising diffusion model, simultaneously learns to both generate and segment images.
no code implementations • 21 Sep 2023 • Haoyu Wang, Xin Yuan, Qinqing Ren
Safety controllers is widely used to achieve safe reinforcement learning.
1 code implementation • 28 Aug 2023 • Jinliang Yuan, Chen Yang, Dongqi Cai, Shihe Wang, Xin Yuan, Zeling Zhang, Xiang Li, Dingge Zhang, Hanzi Mei, Xianqing Jia, Shangguang Wang, Mengwei Xu
Concurrently, each app contributes a concise, offline fine-tuned "adapter" tailored to distinct downstream tasks.
no code implementations • 27 Jul 2023 • Xin Yuan, Linjie Li, JianFeng Wang, Zhengyuan Yang, Kevin Lin, Zicheng Liu, Lijuan Wang
In this paper, we study the denoising diffusion probabilistic model (DDPM) in wavelet space, instead of pixel space, for visual synthesis.
no code implementations • 13 Jul 2023 • Kai Li, Billy Pik Lik Lau, Xin Yuan, Wei Ni, Mohsen Guizani, Chau Yuen
In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understanding and representation to enable seamless, context-aware interactions within mixed-reality environments.
no code implementations • ICCV 2023 • Siming Zheng, Xin Yuan
We consider the problem of video snapshot compressive imaging (SCI), where sequential high-speed frames are modulated by different masks and captured by a single measurement.
no code implementations • 1 Jun 2023 • Jiamian Wang, Zongliang Wu, Yulun Zhang, Xin Yuan, Tao Lin, Zhiqiang Tao
In this work, we tackle this challenge by marrying prompt tuning with FL to snapshot compressive imaging for the first time and propose an federated hardware-prompt learning (FedHP) method.
1 code implementation • NeurIPS 2023 • Zheng Chen, Yulun Zhang, Ding Liu, Bin Xia, Jinjin Gu, Linghe Kong, Xin Yuan
Specifically, we perform the DM in a highly compacted latent space to generate the prior feature for the deblurring process.
2 code implementations • NeurIPS 2023 • Yuanhao Cai, Yuxin Zheng, Jing Lin, Xin Yuan, Yulun Zhang, Haoqian Wang
Finally, our BiSRNet is derived by using the proposed techniques to binarize the base model.
1 code implementation • CVPR 2023 • Lishun Wang, Miao Cao, Xin Yuan
We are the first time to show that an UHD color video with high compression ratio can be reconstructed from a snapshot 2D measurement using a single end-to-end deep learning model with PSNR above 32 dB.
no code implementations • 12 May 2023 • Youyang Qu, Xin Yuan, Ming Ding, Wei Ni, Thierry Rakotoarivelo, David Smith
This inspired recent research on removing the influence of specific data samples from a trained ML model.
1 code implementation • 3 May 2023 • Yulong Wang, Tianxiang Li, Shenghong Li, Xin Yuan, Wei Ni
Deep Neural Networks (DNNs) are vulnerable to adversarial examples, while adversarial attack models, e. g., DeepFool, are on the rise and outrunning adversarial example detection techniques.
no code implementations • 11 Mar 2023 • Yulong Wang, Tong Sun, Shenghong Li, Xin Yuan, Wei Ni, Ekram Hossain, H. Vincent Poor
This survey provides a comprehensive overview of the recent advancements in the field of adversarial attack and defense techniques, with a focus on deep neural network-based classification models.
no code implementations • 7 Mar 2023 • Xin Yuan, Wei Ni, Ming Ding, Kang Wei, Jun Li, H. Vincent Poor
The contribution of the new DP mechanism to the convergence and accuracy of privacy-preserving FL is corroborated, compared to the state-of-the-art Gaussian noise mechanism with a persistent noise amplitude.
no code implementations • 10 Feb 2023 • Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang, Abbas Jamalipour
This paper presents a new deep reinforcement learning (DRL)-based approach to the trajectory planning and jamming rejection of an unmanned aerial vehicle (UAV) for the Internet-of-Things (IoT) applications.
1 code implementation • 26 Jan 2023 • Qingsong Xu, Yilei Shi, Xin Yuan, Xiao Xiang Zhu
Empirical results show that the proposed model is effective and practical for remote sensing image scene classification, regardless of whether the source data is available or not.
no code implementations • 8 Jan 2023 • Daoyu Li, Hanwen Xu, Miao Cao, Xin Yuan, David J. Brady, Liheng Bian
However, the computational cost has inhibited NLR from seeking global structural similarity, which consequentially keeps it trapped in the tradeoff between accuracy and efficiency and prevents it from high-dimensional large-scale tasks.
3 code implementations • 24 Nov 2022 • Zheng Chen, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan
The core of our CAT is the Rectangle-Window Self-Attention (Rwin-SA), which utilizes horizontal and vertical rectangle window attention in different heads parallelly to expand the attention area and aggregate the features cross different windows.
no code implementations • 10 Nov 2022 • Xiaoteng Zhou, Changli Yu, Shihao Yuan, Xin Yuan, Hangchi Yu, Citong Luo
Underwater automatic target recognition (UATR) has been a challenging research topic in ocean engineering.
1 code implementation • 4 Oct 2022 • Jiale Zhang, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan
This is considered as a dense attention strategy since the interactions of tokens are restrained in dense regions.
1 code implementation • 24 Sep 2022 • Jiamian Wang, Kunpeng Li, Yulun Zhang, Xin Yuan, Zhiqiang Tao
By observing this physical encoding procedure, two major challenges stand in the way of a high-fidelity reconstruction.
1 code implementation • 4 Sep 2022 • Lishun Wang, Miao Cao, Yong Zhong, Xin Yuan
In this paper, we consider the reconstruction algorithm in video SCI, i. e., recovering a series of video frames from a compressed measurement.
no code implementations • 19 Aug 2022 • Yulong Wang, Minghui Zhao, Shenghong Li, Xin Yuan, Wei Ni
In this paper, we propose a new backdoor trigger, which is easy to generate, imperceptible, and highly effective.
no code implementations • 17 Aug 2022 • Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, John Collomosse
We develop an approach for text-to-image generation that embraces additional retrieval images, driven by a combination of implicit visual guidance loss and generative objectives.
no code implementations • 27 Jul 2022 • Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang
Being a key technology for beyond fifth-generation wireless systems, joint communication and radar sensing (JCAS) utilizes the reflections of communication signals to detect foreign objects and deliver situational awareness.
1 code implementation • 20 May 2022 • Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Henghui Ding, Yulun Zhang, Radu Timofte, Luc van Gool
In coded aperture snapshot spectral compressive imaging (CASSI) systems, hyperspectral image (HSI) reconstruction methods are employed to recover the spatial-spectral signal from a compressed measurement.
Ranked #1 on Spectral Reconstruction on Real HSI
no code implementations • 7 May 2022 • Yujia Xue, Siming Zheng, Waleed Tahir, Zhengjue Wang, Hao Zhang, Ziyi Meng, Lei Tian, Xin Yuan
We consider the image and video compression on resource limited platforms.
no code implementations • 18 Mar 2022 • Xin Yuan, Yongbing Feng, Mingming Ye, Cheng Tuo, Minghang Zhang
The solution to constructing a custom voice is to combine an adaptive acoustic model with a robust vocoder.
1 code implementation • 17 Mar 2022 • Zhiyuan Zha, Bihan Wen, Xin Yuan, Saiprasad Ravishankar, Jiantao Zhou, Ce Zhu
Furthermore, we present a unified framework for incorporating various GSR and LR models and discuss the relationship between GSR and LR models.
1 code implementation • 9 Mar 2022 • Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
Many algorithms have been developed to solve the inverse problem of coded aperture snapshot spectral imaging (CASSI), i. e., recovering the 3D hyperspectral images (HSIs) from a 2D compressive measurement.
Ranked #2 on Spectral Reconstruction on Real HSI
2 code implementations • CVPR 2022 • Xiaowan Hu, Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
On the one hand, the proposed HR spatial-spectral attention module with its efficient feature fusion provides continuous and fine pixel-level features.
Ranked #5 on Spectral Reconstruction on Real HSI
no code implementations • 1 Mar 2022 • Ruiying Lu, Ziheng Cheng, Bo Chen, Xin Yuan
Video snapshot compressive imaging (SCI) utilizes a 2D detector to capture sequential video frames and compresses them into a single measurement.
1 code implementation • 25 Jan 2022 • Chengshuai Yang, Shiyu Zhang, Xin Yuan
To address these problems, we develop the ensemble learning priors to further improve the reconstruction accuracy and propose the scalable learning to empower deep learning the scalability just like the traditional algorithm.
1 code implementation • 18 Jan 2022 • Yaping Zhao, Siming Zheng, Xin Yuan
The ability of snapshot compressive imaging (SCI) systems to efficiently capture high-dimensional (HD) data has led to an inverse problem, which consists of recovering the HD signal from the compressed and noisy measurement.
1 code implementation • 15 Jan 2022 • Lishun Wang, Zongliang Wu, Yong Zhong, Xin Yuan
Spectral compressive imaging (SCI) is able to encode the high-dimensional hyperspectral image to a 2D measurement, and then uses algorithms to reconstruct the spatio-spectral data-cube.
1 code implementation • 15 Jan 2022 • Siming Zheng, Xiaoyu Yang, Xin Yuan
We consider the reconstruction problem of video compressive sensing (VCS) under the deep unfolding/rolling structure.
1 code implementation • 14 Jan 2022 • Zongliang Wu, Chengshuai Yang, Xiongfei Su, Xin Yuan
Towards this end, in this work, we propose the online PnP algorithm which can adaptively update the network's parameters within the PnP iteration; this makes the denoising network more applicable to the desired data in the SCI reconstruction.
1 code implementation • 31 Dec 2021 • Jiamian Wang, Yulun Zhang, Xin Yuan, Ziyi Meng, Zhiqiang Tao
Recently, hyperspectral imaging (HSI) has attracted increasing research attention, especially for the ones based on a coded aperture snapshot spectral imaging (CASSI) system.
no code implementations • 29 Nov 2021 • Xiaoteng Zhou, Changli Yu, Xin Yuan, Haijun Feng, Yang Xu
In the field of deep-sea exploration, sonar is presently the only efficient long-distance sensing device.
no code implementations • 17 Nov 2021 • Xiaoteng Zhou, Changli Yu, Xin Yuan, Yi Wu, Haijun Feng, Citong Luo
In the field of deep-sea exploration, sonar is presently the only efficient long-distance sensing device.
3 code implementations • CVPR 2022 • Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
The HSI representations are highly similar and correlated across the spectral dimension.
Ranked #2 on Spectral Reconstruction on ARAD-1K
no code implementations • 29 Sep 2021 • Jiamian Wang, Yulun Zhang, Xin Yuan, Yun Fu, Zhiqiang Tao
As the inverse process of snapshot compressive imaging, the hyperspectral image (HSI) reconstruction takes the 2D measurement as input and posteriorly retrieves the captured 3D spatial-spectral signal.
no code implementations • 18 Sep 2021 • Jinli Suo, Weihang Zhang, Jin Gong, Xin Yuan, David J. Brady, Qionghai Dai
Signal capture stands in the forefront to perceive and understand the environment and thus imaging plays the pivotal role in mobile vision.
1 code implementation • 11 Sep 2021 • Ruiying Lu, Bo Chen, Guanliang Liu, Ziheng Cheng, Mu Qiao, Xin Yuan
In this paper, we propose an optical flow-aided recurrent neural network for dual video SCI systems, which provides high-quality decoding in seconds.
1 code implementation • ICCV 2021 • Ziyi Meng, Zhenming Yu, Kun Xu, Xin Yuan
In this paper, inspired by the untrained neural networks such as deep image priors (DIP) and deep decoders, we develop a framework by integrating DIP into the plug-and-play regime, leading to a self-supervised network for spectral SCI reconstruction.
no code implementations • 27 Aug 2021 • Xiaoteng Zhou, Changli Yu, Xin Yuan, Citong Luo
This paper proposes a method that combines the style transfer technique and the learned descriptor to enhance the matching performances of underwater sonar images.
no code implementations • 27 Aug 2021 • Xiaoteng Zhou, Changli Yu, Xin Yuan, Citong Luo
Subsea images measured by the side scan sonars (SSSs) are necessary visual data in the process of deep-sea exploration by using the autonomous underwater vehicles (AUVs).
no code implementations • 27 Aug 2021 • Xiaoteng Zhou, Changli Yu, Xin Yuan, Citong Luo
Additionally, the method is based on the combination of image depth semantic layer, and it could indirectly display the local feature matching relationship between original image pair, which provides a new solution to the underwater multi-sensor image matching problem.
1 code implementation • 17 Aug 2021 • Jiamian Wang, Yulun Zhang, Xin Yuan, Yun Fu, Zhiqiang Tao
The emerging technology of snapshot compressive imaging (SCI) enables capturing high dimensional (HD) data in an efficient way.
1 code implementation • 30 Jun 2021 • Zhihong Zhang, Chao Deng, Yang Liu, Xin Yuan, Jinli Suo, Qionghai Dai
Towards this end, snapshot compressive imaging (SCI) was proposed as a promising solution to improve the throughput of imaging systems by compressive sampling and computational reconstruction.
no code implementations • 18 May 2021 • Sidi Lu, Xin Yuan, Aggelos K Katsaggelos, Weisong Shi
We apply reinforcement learning to video compressive sensing to adapt the compression ratio.
no code implementations • CVPR 2021 • Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, Yilin Wang, Michael Maire, Ajinkya Kale, Baldo Faieta
We first train our model on COCO and evaluate the learned visual representations on various downstream tasks including image classification, object detection, and instance segmentation.
1 code implementation • ICCV 2021 • Xiu Li, Jinli Suo, Weihang Zhang, Xin Yuan, Qionghai Dai
High quality imaging usually requires bulky and expensive lenses to compensate geometric and chromatic aberrations.
1 code implementation • CVPR 2021 • Tao Huang, Weisheng Dong, Xin Yuan, Jinjian Wu, Guangming Shi
Different from existing GSM models using hand-crafted scale priors (e. g., the Jeffrey's prior), we propose to learn the scale prior through a deep convolutional neural network (DCNN).
no code implementations • 7 Mar 2021 • Xin Yuan, David J. Brady, Aggelos K. Katsaggelos
Via novel optical designs, the 2D detector samples the HD data in a {\em compressive} manner; following this, algorithms are employed to reconstruct the desired HD data-cube.
2 code implementations • CVPR 2021 • Ziheng Cheng, Bo Chen, Guanliang Liu, Hao Zhang, Ruiying Lu, Zhengjue Wang, Xin Yuan
With the knowledge of masks, optimization algorithms or deep learning methods are employed to reconstruct the desired high-speed video frames from this snapshot measurement.
2 code implementations • CVPR 2021 • Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen, Xin Yuan
To capture high-speed videos using a two-dimensional detector, video snapshot compressive imaging (SCI) is a promising system, where the video frames are coded by different masks and then compressed to a snapshot measurement.
1 code implementation • 13 Jan 2021 • Xin Yuan, Yang Liu, Jinli Suo, Frédo Durand, Qionghai Dai
On the other hand, applying SCI to large-scale problems (HD or UHD videos) in our daily life is still challenging and one of the bottlenecks lies in the reconstruction algorithm.
no code implementations • 30 Dec 2020 • wei he, Naoto Yokoya, Xin Yuan
Specifically, the RGB measurement is utilized to estimate the coefficients, meanwhile the CASSI measurement is adopted to provide the orthogonal spectral basis.
1 code implementation • 13 Dec 2020 • Ziyi Meng, Shirin Jalali, Xin Yuan
The hardware encoder typically consists of an (optical) imaging system designed to capture {compressed measurements}.
no code implementations • 3 Dec 2020 • Zaid ALzaid, Xin Yuan, Saptarshi Bhowmik
The Jellyfish network has recently be proposed as an alternate to the fat-tree network as the interconnect for data centers and high performance computing clusters.
Networking and Internet Architecture Distributed, Parallel, and Cluster Computing
no code implementations • SEMEVAL 2020 • Weilong Chen, Xin Yuan, Sai Zhang, Jiehui Wu, Yanru Zhang, Yan Wang
Word similarity is widely used in machine learning applications like searching engine and recommendation.
1 code implementation • 23 Nov 2020 • Zheng Wang, Xin Yuan, Toshihiko Yamasaki, Yutian Lin, Xin Xu, Wenjun Zeng
In essence, current re-ID overemphasizes the importance of retrieval but underemphasizes that of verification, \textit{i. e.}, all returned images are considered as the target.
1 code implementation • 13 Oct 2020 • Abu Naser, Mehran Sadeghi Lahijani, Cong Wu, Mohsen Gavahi, Viet Tung Hoang, Zhi Wang, Xin Yuan
In order for High-Performance Computing (HPC) applications with data security requirements to execute in the public cloud, the cloud infrastructure must ensure the privacy and integrity of data.
Distributed, Parallel, and Cluster Computing Cryptography and Security
1 code implementation • 13 Oct 2020 • Abu Naser, Cong Wu, Mehran Sadeghi Lahijani, Mohsen Gavahi, Viet Tung Hoang, Zhi Wang, Xin Yuan
The cloud infrastructure must provide security for High-Performance Computing (HPC) applications of sensitive data to execute in such an environment.
Distributed, Parallel, and Cluster Computing Cryptography and Security
no code implementations • 20 Aug 2020 • Qingsong Xu, Xin Yuan, Chaojun Ouyang, Yue Zeng
First, a novel segmentation framework, called the heavy-weight spatial feature fusion pyramid network (FFPNet), is proposed to address the spatial problem of high-resolution remote sensing images.
no code implementations • ICLR 2021 • Xin Yuan, Pedro Savarese, Michael Maire
We develop an approach to growing deep network architectures over the course of training, driven by a principled combination of accuracy and sparsity objectives.
no code implementations • 16 May 2020 • Zhiyuan Zha, Xin Yuan, Joey Tianyi Zhou, Jiantao Zhou, Bihan Wen, Ce Zhu
In this paper, we propose a joint low-rank and deep (LRD) image model, which contains a pair of triply complementary priors, namely \textit{external} and \textit{internal}, \textit{deep} and \textit{shallow}, and \textit{local} and \textit{non-local} priors.
no code implementations • 16 May 2020 • Xin Yuan
Various TV denoising and projection algorithms are developed and tested for video SCI reconstruction on both simulation and real datasets.
3 code implementations • CVPR 2020 • Xin Yuan, Yang Liu, Jinli Suo, Qionghai Dai
Snapshot compressive imaging (SCI) aims to capture the high-dimensional (usually 3D) images using a 2D sensor (detector) in a single snapshot.
no code implementations • 17 Nov 2019 • Yilang Zhang, Neal N. Xiong, Zheng Wei, Xin Yuan, Jian Wang
The augmented images help to tell apart the edge gradients, edge pixels and non-edge ones in log-histogram, which contribute significantly to the feature extraction and color-ambiguity elimination, thereby advancing the accuracy of illuminant estimation.
no code implementations • 23 Sep 2019 • Pravir Singh Gupta, Xin Yuan, Gwan Seong Choi
Bearing these concerns in mind, we propose DRCAS (Deep Restoration network for hardware based Compressed Acquisition Scheme), which to our best knowledge, is the first work proposed in the literature for restoration of images acquired using acquisition scheme like HCAS.
no code implementations • NeurIPS Workshop Deep_Invers 2019 • Pei Peng, Shirin Jalali, Xin Yuan
Compressed sensing is about recovering a structured high-dimensional signal ${\bf x}\in R^n$ from its under-determined noisy linear measurements ${\bf y}\in R^m$, where $m\ll n$.
no code implementations • CVPR 2019 • Xin Yuan, Liangliang Ren, Jiwen Lu, Jie Zhou
In this paper, we propose an Enhanced Bayesian Compression method to flexibly compress the deep networks via reinforcement learning.
no code implementations • ECCV 2018 • Xin Yuan, Liangliang Ren, Jiwen Lu, Jie zhou
In this paper, we propose a simple yet effective relaxation-free method to learn more effective binary codes via policy gradient for scalable image search.
no code implementations • ECCV 2018 • Liangliang Ren, Xin Yuan, Jiwen Lu, Ming Yang, Jie Zhou
Visual tracking is confronted by the dilemma to locate a target both}accurately and efficiently, and make decisions online whether and how to adapt the appearance model or even restart tracking.
3 code implementations • 20 Jul 2018 • Yang Liu, Xin Yuan, Jinli Suo, David J. Brady, Qionghai Dai
We further investigate the special structure of the sampling process in SCI to tackle the computational workload and memory issues in SCI reconstruction.
1 code implementation • 6 Jul 2018 • Zhiyuan Zha, Xin Yuan, Bihan Wen, Jiantao Zhou, Jiachao Zhang, Ce Zhu
Towards this end, we first obtain a good reference of the original image groups by using the image NSS prior, and then the rank residual of the image groups between this reference and the degraded image is minimized to achieve a better estimate to the desired image.
no code implementations • CVPR 2018 • Zhixiang Chen, Xin Yuan, Jiwen Lu, Qi Tian, Jie zhou
This paper presents a discrepancy minimizing model to address the discrete optimization problem in hashing learning.
no code implementations • 22 Mar 2018 • Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Yechao Bai, Lan Tang, Xin Yuan
Inspired by group-based sparse coding, recently proposed group sparsity residual (GSR) scheme has demonstrated superior performance in image processing.
no code implementations • CVPR 2018 • Xinyuan Zhang, Xin Yuan, Lawrence Carin
Low-rank signal modeling has been widely leveraged to capture non-local correlation in image processing applications.
no code implementations • 12 Sep 2017 • Zhiyuan Zha, Xin Yuan, Bihan Wen, Jiantao Zhou, Jiachao Zhang, Ce Zhu
Sparse coding has achieved a great success in various image processing tasks.
no code implementations • 3 Jun 2017 • Xin Yuan, Raziel Haimi-Cohen
We present an end-to-end image compression system based on compressive sensing.
no code implementations • 15 Feb 2017 • Zhiyuan Zha, Xin Yuan, Bei Li, Xinggan Zhang, Xin Liu, Lan Tang, Ying-Chang Liang
However, it still lacks a sound mathematical explanation on why WNNM is more feasible than NNM.
no code implementations • 19 Jan 2017 • Xin Yuan, Gang Huang, Hong Jiang, Paul Wilford
2) The coding patterns used in each block can be the same, therefore the sensing matrix is only of the block size compared to the entire image size in existing $\text{L}^2\text{C}^2$.
no code implementations • 11 Jan 2017 • Xin Yuan, Yunchen Pu, Lawrence Carin
During reconstruction and testing, we project the upper layer dictionary to the data level and only a single layer deconvolution is required.
no code implementations • NeurIPS 2016 • Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin
A novel variational autoencoder is developed to model images, as well as associated labels or captions.
no code implementations • 23 Dec 2015 • Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin
A deep generative model is developed for representation and analysis of images, based on a hierarchical convolutional dictionary-learning framework.
no code implementations • 27 Aug 2015 • Xin Yuan, Hong Jiang, Gang Huang, Paul A. Wilford
We develop a new compressive sensing (CS) inversion algorithm by utilizing the Gaussian mixture model (GMM).
no code implementations • 14 Aug 2015 • Xin Yuan, Hong Jiang, Gang Huang, Paul Wilford
We develop a lensless compressive imaging architecture, which consists of an aperture assembly and a single sensor, without using any lens.
no code implementations • 28 Apr 2015 • Xin Yuan, Ricardo Henao, Ephraim L. Tsalik, Raymond J. Langley, Lawrence Carin
A Bayesian model based on the ranks of the data is proposed.
no code implementations • 15 Apr 2015 • Yunchen Pu, Xin Yuan, Lawrence Carin
A generative model is developed for deep (multi-layered) convolutional dictionary learning.
no code implementations • 22 Feb 2015 • Xin Yuan, Tsung-Han Tsai, Ruoyu Zhu, Patrick Llull, David Brady, Lawrence Carin
By using RGB images as side information of the compressive sensing system, the proposed approach is extended to learn a coupled dictionary from the joint dataset of the compressed measurements and the corresponding RGB images, to improve reconstruction quality.
no code implementations • 18 Dec 2014 • Yunchen Pu, Xin Yuan, Lawrence Carin
A generative Bayesian model is developed for deep (multi-layer) convolutional dictionary learning.
no code implementations • 1 Dec 2014 • Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues
These conditions, which are reminiscent of the well-known Slepian-Wolf and Wyner-Ziv conditions, are a function of the number of linear features extracted from the signal of interest, the number of linear features extracted from the side information signal, and the geometry of these signals and their interplay.
no code implementations • NeurIPS 2014 • Ricardo Henao, Xin Yuan, Lawrence Carin
A new Bayesian formulation is developed for nonlinear support vector machines (SVMs), based on a Gaussian process and with the SVM hinge loss expressed as a scaled mixture of normals.
no code implementations • 12 Oct 2014 • Xin Yuan, Patrick Llull, David J. Brady, Lawrence Carin
A Bayesian compressive sensing framework is developed for video reconstruction based on the color coded aperture compressive temporal imaging (CACTI) system.
no code implementations • CVPR 2014 • Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, Guillermo Sapiro, David J. Brady, Lawrence Carin
A simple and inexpensive (low-power and low-bandwidth) modification is made to a conventional off-the-shelf color video camera, from which we recover {multiple} color frames for each of the original measured frames, and each of the recovered frames can be focused at a different depth.
no code implementations • 11 Jan 2014 • Xin Yuan, Vinayak Rao, Shaobo Han, Lawrence Carin
The method we consider in detail, and for which numerical results are presented, is based on increments of a gamma process.
no code implementations • 14 Feb 2013 • Xin Yuan, Jianbo Yang, Patrick Llull, Xuejun Liao, Guillermo Sapiro, David J. Brady, Lawrence Carin
This paper introduces the concept of adaptive temporal compressive sensing (CS) for video.