no code implementations • 23 Jan 2024 • Ali Mottaghi, Mohammad Abdullah Jamal, Serena Yeung, Omid Mohareri
Our method's effectiveness is validated through extensive experiments on benchmark datasets such as DomainNet, Office-Home, and VisDA-C, where AdaEmbed consistently outperforms all the baselines, setting a new state of the art for SSDA.
no code implementations • 10 Dec 2023 • Orr Zohar, Alejandro Lozano, Shelly Goel, Serena Yeung, Kuan-Chieh Wang
We exploit the inherent connection between classes in application-driven datasets and introduce a novel method, Foundation Object detection Model for the Open world, or FOMO, which identifies unknown objects based on their shared attributes with the base known objects.
no code implementations • 14 Sep 2023 • James Burgess, Kuan-Chieh Wang, Serena Yeung
Our method, Viewpoint Neural Textual Inversion (ViewNeTI), controls the 3D viewpoint of objects in generated images from frozen diffusion models.
no code implementations • ICCV 2023 • Jeffrey Gu, Kuan-Chieh Wang, Serena Yeung
Neural fields, which represent signals as a function parameterized by a neural network, are a promising alternative to traditional discrete vector or grid-based representations.
1 code implementation • NeurIPS 2023 • Orr Zohar, Shih-Cheng Huang, Kuan-Chieh Wang, Serena Yeung
As the number of open-source VLM variants increases, there is a need for an efficient model selection strategy that does not require access to a curated evaluation dataset.
1 code implementation • 27 May 2023 • Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung
Language models have been shown to exhibit positive scaling, where performance improves as models are scaled up in terms of size, compute, or data.
no code implementations • 25 May 2023 • Zhenzhen Weng, Zeyu Wang, Serena Yeung
Recent advancements in text-to-image generation have enabled significant progress in zero-shot 3D shape generation.
no code implementations • 11 May 2023 • Pascal Mettes, Mina Ghadimi Atigh, Martin Keller-Ressel, Jeffrey Gu, Serena Yeung
In this paper, we provide a categorization and in-depth overview of current literature on hyperbolic learning for computer vision.
1 code implementation • 2 Apr 2023 • Alexander Ke, Shih-Cheng Huang, Chloe P O'Connell, Michal Klimont, Serena Yeung, Pranav Rajpurkar
We demonstrate video pretraining improves the average performance of seven 3D models on two chest CT datasets, regardless of finetuning dataset size, and that video pretraining allows 3D models to outperform 2D baselines.
1 code implementation • 8 Feb 2023 • Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung
Our proposed method can discover high-error data slices, identify influential attributes and further rectify undesirable model behaviors, without requiring any visual data.
1 code implementation • 8 Feb 2023 • Yuhui Zhang, Shih-Cheng Huang, Zhengping Zhou, Matthew P. Lungren, Serena Yeung
Given the prevalence of 3D medical imaging technologies such as MRI and CT that are widely used in diagnosing and treating diverse diseases, 3D segmentation is one of the fundamental tasks of medical image analysis.
no code implementations • CVPR 2023 • Kuan-Chieh Wang, Zhenzhen Weng, Maria Xenochristou, João Pedro Araújo, Jeffrey Gu, Karen Liu, Serena Yeung
Empirically, we show that NeMo can recover 3D motion in sports using videos from the Penn Action dataset, where NeMo outperforms existing HMR methods in terms of 2D keypoint detection.
1 code implementation • 28 Dec 2022 • Kuan-Chieh Wang, Zhenzhen Weng, Maria Xenochristou, Joao Pedro Araujo, Jeffrey Gu, C. Karen Liu, Serena Yeung
Empirically, we show that NeMo can recover 3D motion in sports using videos from the Penn Action dataset, where NeMo outperforms existing HMR methods in terms of 2D keypoint detection.
1 code implementation • CVPR 2023 • Orr Zohar, Kuan-Chieh Wang, Serena Yeung
The resulting Probabilistic Objectness transformer-based open-world detector, PROB, integrates our framework into traditional object detection models, adapting them for the open-world setting.
1 code implementation • NeurIPS 2023 • Mark Mazumder, Colby Banbury, Xiaozhe Yao, Bojan Karlaš, William Gaviria Rojas, Sudnya Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Smriti Raje, Max Bartolo, Sabri Eyuboglu, Amirata Ghorbani, Emmett Goodman, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen Paritosh, Lilith Bat-Leah, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Ng, Peter Mattson, Vijay Janapa Reddi
Machine learning research has long focused on models rather than datasets, and prominent datasets are used for common ML tasks without regard to the breadth, difficulty, and faithfulness of the underlying problems.
no code implementations • 7 Jul 2022 • Ali Mottaghi, Aidean Sharghi, Serena Yeung, Omid Mohareri
We propose a new domain adaptation method to improve the performance of the surgical activity recognition model in a new operating room for which we only have unlabeled videos.
1 code implementation • 21 Jun 2022 • Zhenzhen Weng, Kuan-Chieh Wang, Angjoo Kanazawa, Serena Yeung
The ability to perceive 3D human bodies from a single image has a multitude of applications ranging from entertainment and robotics to neuroscience and healthcare.
2 code implementations • 3 Mar 2022 • Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Zou
Our systematic analysis demonstrates that this gap is caused by a combination of model initialization and contrastive learning optimization.
no code implementations • 14 Dec 2021 • Emmett D. Goodman, Krishna K. Patel, Yilun Zhang, William Locke, Chris J. Kennedy, Rohan Mehrotra, Stephen Ren, Melody Guan, Maren Downing, Hao Wei Chen, Jevin Z. Clark, Gabriel A. Brat, Serena Yeung
Open procedures represent the dominant form of surgery worldwide.
no code implementations • 20 Nov 2021 • Julia Gong, F. Christopher Holsinger, Serena Yeung
In contrast to prior work that uses full optical flow, we introduce a new foreground-targeted visual warping approach that learns flow fields from VOS data.
no code implementations • 8 Jul 2021 • Jeffrey Gu, Serena Yeung
Creating representations of shapes that are invari-ant to isometric or almost-isometric transforma-tions has long been an area of interest in shape anal-ysis, since enforcing invariance allows the learningof more effective and robust shape representations. Most existing invariant shape representations arehandcrafted, and previous work on learning shaperepresentations do not focus on producing invariantrepresentations.
1 code implementation • CVPR 2021 • Joy Hsu, Wah Chiu, Serena Yeung
In the biomedical domain, there is an abundance of dense, complex data where objects of interest may be challenging to detect or constrained by limits of human knowledge.
no code implementations • CVPR 2021 • Zhenzhen Weng, Mehmet Giray Ogut, Shai Limonchik, Serena Yeung
Instance segmentation is an active topic in computer vision that is usually solved by using supervised learning approaches over very large datasets composed of object level masks.
Ranked #5 on Novel Object Detection on LVIS v1.0 val
2 code implementations • ICCV 2021 • Shih-Cheng Huang, Liyue Shen, Matthew P. Lungren, Serena Yeung
In recent years, the growing number of medical imaging studies is placing an ever-increasing burden on radiologists.
3 code implementations • ICLR 2021 • Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, Jose M. Alvarez
While federated learning traditionally aims to train a single global model across decentralized local datasets, one model may not always be ideal for all participating clients.
no code implementations • 13 Dec 2020 • Michael Zhang, Xiaotian Cheng, Daniel Copeland, Arjun Desai, Melody Y. Guan, Gabriel A. Brat, Serena Yeung
A state-of-the-art convolutional neural network architecture for object detection was used to detect operating hands in open surgery videos.
no code implementations • NeurIPS 2021 • Joy Hsu, Jeffrey Gu, Gong-Her Wu, Wah Chiu, Serena Yeung
To that end, we consider encoder-decoder architectures with a hyperbolic latent space, to explicitly capture hierarchical relationships present in subvolumes of the data.
1 code implementation • CVPR 2021 • Zhenzhen Weng, Serena Yeung
Indeed, from a single image of a person placed in an indoor scene, we as humans are adept at resolving ambiguities of the human pose and room layout through our knowledge of the physical laws and prior perception of the plausible object and human poses.
no code implementations • 12 Nov 2020 • Ali Mottaghi, Prathusha K Sarma, Xavier Amatriain, Serena Yeung, Anitha Kannan
We study the problem of medical symptoms recognition from patient text, for the purposes of gathering pertinent information from the patient (known as history-taking).
no code implementations • 28 Sep 2020 • Joy Hsu, Jeffrey Gu, Gong Her Wu, Wah Chiu, Serena Yeung
There exists a need for unsupervised 3D segmentation on complex volumetric data, particularly when annotation ability is limited or discovery of new categories is desired.
no code implementations • 23 Feb 2020 • Sabina Tomkins, Peng Liao, Predrag Klasnja, Serena Yeung, Susan Murphy
In mobile health (mHealth), reinforcement learning algorithms that adapt to one's context without learning personalized policies might fail to distinguish between the needs of individuals.
1 code implementation • 20 Dec 2019 • Ali Mottaghi, Serena Yeung
Active learning aims to develop label-efficient algorithms by querying the most informative samples to be labeled by an oracle.
no code implementations • 25 Nov 2018 • Edward Chou, Josh Beal, Daniel Levy, Serena Yeung, Albert Haque, Li Fei-Fei
Homomorphic encryption enables arbitrary computation over data while it remains encrypted.
Cryptography and Security
no code implementations • ECCV 2018 • Michelle Guo, Edward Chou, De-An Huang, Shuran Song, Serena Yeung, Li Fei-Fei
We propose Neural Graph Matching (NGM) Networks, a novel framework that can learn to recognize a previous unseen 3D action class with only a few examples.
Ranked #1 on Skeleton Based Action Recognition on CAD-120
no code implementations • ECCV 2018 • Bingbin Liu, Serena Yeung, Edward Chou, De-An Huang, Li Fei-Fei, Juan Carlos Niebles
A major challenge in computer vision is scaling activity understanding to the long tail of complex activities without requiring collecting large quantities of data for new actions.
no code implementations • ECCV 2018 • Michelle Guo, Albert Haque, De-An Huang, Serena Yeung, Li Fei-Fei
We propose dynamic task prioritization for multitask learning.
2 code implementations • 24 Feb 2018 • Amy Jin, Serena Yeung, Jeffrey Jopling, Jonathan Krause, Dan Azagury, Arnold Milstein, Li Fei-Fei
We show that our method both effectively detects the spatial bounds of tools as well as significantly outperforms existing methods on tool presence detection.
no code implementations • 1 Aug 2017 • Albert Haque, Michelle Guo, Alexandre Alahi, Serena Yeung, Zelun Luo, Alisha Rege, Jeffrey Jopling, Lance Downing, William Beninati, Amit Singh, Terry Platchek, Arnold Milstein, Li Fei-Fei
One in twenty-five patients admitted to a hospital will suffer from a hospital acquired infection.
no code implementations • CVPR 2017 • Katsuyuki Nakamura, Serena Yeung, Alexandre Alahi, Li Fei-Fei
Physiological signals such as heart rate can provide valuable information about an individual's state and activity.
no code implementations • 9 Jun 2017 • Serena Yeung, Anitha Kannan, Yann Dauphin, Li Fei-Fei
The so-called epitomes of this model are groups of mutually exclusive latent factors that compete to explain the data.
no code implementations • CVPR 2017 • Serena Yeung, Vignesh Ramanathan, Olga Russakovsky, Liyue Shen, Greg Mori, Li Fei-Fei
Our method uses Q-learning to learn a data labeling policy on a small labeled training dataset, and then uses this to automatically label noisy web data for new visual concepts.
2 code implementations • 23 Mar 2016 • Albert Haque, Boya Peng, Zelun Luo, Alexandre Alahi, Serena Yeung, Li Fei-Fei
We propose a viewpoint invariant model for 3D human pose estimation from a single depth image.
Ranked #4 on Pose Estimation on ITOP top-view
1 code implementation • CVPR 2016 • Serena Yeung, Olga Russakovsky, Greg Mori, Li Fei-Fei
In this work we introduce a fully end-to-end approach for action detection in videos that learns to directly predict the temporal bounds of actions.
Ranked #9 on Temporal Action Localization on THUMOS’14 (mAP IOU@0.2 metric)
1 code implementation • 21 Jul 2015 • Serena Yeung, Olga Russakovsky, Ning Jin, Mykhaylo Andriluka, Greg Mori, Li Fei-Fei
Every moment counts in action recognition.
Ranked #7 on Action Detection on Multi-THUMOS
no code implementations • 23 Jun 2014 • Serena Yeung, Alireza Fathi, Li Fei-Fei
In this paper we present VideoSET, a method for Video Summary Evaluation through Text that can evaluate how well a video summary is able to retain the semantic information contained in its original video.