Recent Work

Google Scholar

  • 2024

    • Nate Gillman, Michael Freeman, Daksh Aggarwal, Chia-Hong Hsu, Calvin Luo, Yonglong Tian, and Chen Sun, Self-Correcting Self-Consuming Loops for Generative Model Training. International Conference on Machine Learning (ICML) 2024 [arXiv] [Project]
    • Qi Zhao*, Shijie Wang*, Ce Zhang, Changcheng Fu, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, and Chen Sun, AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos? International Conference on Learning Representations (ICLR) 2024 [arXiv] [Project]
    • Ce Zhang*, Changcheng Fu*, Shijie Wang, Nakul Agarwal, Kwonjoon Lee, Chiho Choi, and Chen Sun, Object-centric Video Representation for Long-term Action Anticipation. Winter Conference on Applications of Computer Vision (WACV) 2024 [arXiv] [Code]
    • Yunhao Luo, Chen Sun, Joshua B. Tenenbaum, and Yilun Du, Potential Based Diffusion Motion Planning. International Conference on Machine Learning (ICML) 2024
    • Jiarui Xu, Xingyi Zhou, Shen Yan, Xiuye Gu, Anurag Arnab, Chen Sun, Xiaolong Wang, and Cordelia Schmid, Pixel Aligned Language Models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2024 [arXiv] [Project]
    • Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, and Anurag Arnab, End-to-End Spatio-Temporal Action Localisation with Video Transformers. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2024 [arXiv]
  • 2023

    • Tian Yun*, Zilai Zeng*, Kunal Handa, Ashish V Thapliyal, Bo Pang, Ellie Pavlick, and Chen Sun, Emergence of Abstract State Representations in Embodied Sequence Modeling. Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023 [arXiv] [Code]
    • Apoorv Khandelwal, Ellie Pavlick, and Chen Sun, Analyzing Modular Approaches for Visual Question Decomposition. Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023 [arXiv] [Code]
    • Zilai Zeng, Ce Zhang, Shijie Wang, and Chen Sun, Goal-Conditioned Predictive Coding for Offline Reinforcement Learning. Conference on Neural Information Processing Systems (NeurIPS) 2023 [arXiv] [Code]
    • Chen Sun, Calvin Luo, Xingyi Zhou, Anurag Arnab, and Cordelia Schmid, Does Visual Pretraining Help End-to-End Reasoning? Conference on Neural Information Processing Systems (NeurIPS) 2023 [arXiv]
    • Ziniu Hu, Ahmet Iscen, Chen Sun, Kai-Wei Chang, Yizhou Sun, David A Ross, Cordelia Schmid, and Alireza Fathi, AVIS: Autonomous Visual Information Seeking with Large Language Models. Conference on Neural Information Processing Systems (NeurIPS) 2023 [arXiv]
    • Tian Yun, Usha Bhalla, Ellie Pavlick, and Chen Sun, Do Vision-Language Pretrained Models Learn Primitive Concepts? Transactions on Machine Learning Research (TMLR) [arXiv] [Project]
    • Xingyi Zhou, Anurag Arnab, Chen Sun, and Cordelia Schmid, How Can Objects Help Action Recognition? IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023 [arXiv]
    • Ziniu Hu, Ahmet Iscen, Chen Sun, Zirui Wang, Kai-Wei Chang, Yizhou Sun, Cordelia Schmid, David A Ross, and Alireza Fathi, REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023 [arXiv]
  • 2022

    • Arsha Nagrani, Paul Hongsuck Seo, Bryan Seybold, Anja Hauth, Santiago Manen, Chen Sun, and Cordelia Schmid, Learning Audio-Video Modalities from Image Captions. European Conference on Computer Vision (ECCV) 2022 [arXiv]
    • Medhini Narasimhan, Arsha Nagrani, Chen Sun, Michael Rubinstein, Trevor Darrell, Anna Rohrbach, and Cordelia Schmid, Summarizing Instructional Videos with Task Relevance and Cross-Modal Saliency. European Conference on Computer Vision (ECCV) 2022
    • Dylan Ebert, Chen Sun, and Ellie Pavlick, Do Trajectories Encode Verb Meaning? Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) 2022 [arXiv] [data]
    • Valentin Gabeur, Paul Hongsuck Seo, Arsha Nagrani, Chen Sun, Karteek Alahari, and Cordelia Schmid, AVATAR: Unconstrained Audiovisual Speech Recognition. Conference of the International Speech Communication Association (INTERSPEECH) 2022 [arXiv]
    • Shen Yan, Xuehan Xiong, Anurag Arnab, Zhichao Lu, Mi Zhang, Chen Sun, and Cordelia Schmid, Multiview Transformers for Video Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022 [pdf]
    • Valentin Gabeur, Arsha Nagrani, Chen Sun, Karteek Alahari, and Cordelia Schmid, Masking Modalities for Cross-modal Video Retrieval. Winter Conference on Applications of Computer Vision (WACV) 2022 [arXiv]
  • 2021

    • Arsha Nagrani, Shan Yang, Anurag Arnab, Aren Jansen, Cordelia Schmid, and Chen Sun, Attention Bottlenecks for Multimodal Fusion. Conference on Neural Information Processing Systems (NeurIPS) 2021 [arXiv]
    • Tian Yun, Chen Sun, and Ellie Pavlick, Does Vision-and-Language Pretraining Improve Lexical Grounding? Findings of EMNLP 2021 [arXiv]
    • Alexander Pashevich, Cordelia Schmid, and Chen Sun, Episodic Transformer for Vision-and-Language Navigation. International Conference on Computer Vision (ICCV) 2021 [arXiv]
    • Dave Epstein, Jiajun Wu, Cordelia Schmid, and Chen Sun, Learning Temporal Dynamics from Cycles in Narrated Video. International Conference on Computer Vision (ICCV) 2021 [arXiv]
    • Chen Sun, Arsha Nagrani, Yonglong Tian, and Cordelia Schmid, Composable Augmentation Encoding for Video Representation Learning. International Conference on Computer Vision (ICCV) 2021 [arXiv]
    • Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, and Cordelia Schmid, ViViT: A Video Vision Transformer. International Conference on Computer Vision (ICCV) 2021 [arXiv]
    • Anurag Arnab, Chen Sun, and Cordelia Schmid, Unified Graph Structured Models for Video Understanding. International Conference on Computer Vision (ICCV) 2021 [arXiv]
    • Junru Gu, Chen Sun, and Hang Zhao, DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets. International Conference on Computer Vision (ICCV) 2021 [arXiv]
    • Lu Mi, et al., HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021 [pdf]
    • Jack Valmadre, Alex Bewley, Jonathan Huang, Chen Sun, Cristian Sminchisescu, and Cordelia Schmid, Local Metrics for Multi-Object Tracking. arXiv:2104.02631 [arXiv]
  • 2020

    • Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li and Dragomir Anguelov, TNT: Target-driveN Trajectory Prediction. Conference on Robot Learning (CoRL) 2020 [arXiv]
    • Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid and Phillip Isola, What makes for good views for contrastive learning. Conference on Neural Information Processing Systems (NeurIPS) 2020 [arXiv] [Project] [Code]
    • Anurag Arnab, Chen Sun, Arsha Nagrani and Cordelia Schmid, Uncertainty-Aware Weakly Supervised Action Detection from Untrimmed Videos. European Conference on Computer Vision (ECCV) 2020 [arXiv]
    • Valentin Gabeur, Chen Sun, Karteek Alahari and Cordelia Schmid, Multi-modal Transformer for Video Retrieval. European Conference on Computer Vision (ECCV) 2020 [arXiv] [Project][Code]
    • Arsha Nagrani, Chen Sun, David Ross, Rahul Sukthankar, Cordelia Schmid and Andrew Zisserman, Speech2Action: Cross-modal Supervision for Action Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020 [arXiv] [Project] [Data]
    • Jiyang Gao*, Chen Sun*, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li and Cordelia Schmid, VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020 [arXiv] [Blog] [VentureBeat]
    • Jonathan C Stroud, David A Ross, Chen Sun, Jia Deng, and Rahul Sukthankar, D3D: Distilled 3D Networks for Video Action Recognition. Winter Conference on Applications of Computer Vision (WACV) 2020 [arXiv] [Project] [Code] [Checkpoints]
    • Jonathan C. Stroud, David A. Ross, Chen Sun, Jia Deng, Rahul Sukthankar and Cordelia Schmid, Learning Video Representations from Textual Web Supervision. arXiv:2007.14937 [arXiv]
  • 2019

    • Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin Murphy, and Honglak Lee, Unsupervised Learning of Object Structure and Dynamics from Videos. Conference on Neural Information Processing Systems (NeurIPS) 2019 [arXiv] [Project] [Code]
    • Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy, and Cordelia Schmid, VideoBERT: A Joint Model for Video and Language Representation Learning. International Conference on Computer Vision (ICCV) 2019 [arXiv] [Blog] [VentureBeat]
    • Chen Sun, Abhinav Shrivastava, Carl Vondrick, Rahul Sukthankar, Kevin Murphy, and Cordelia Schmid, Relational Action Forecasting. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 (best paper finalist) [arXiv]
    • Nam Vo, Lu Jiang, Chen Sun, Kevin Murphy, Li-Jia Li, Li Fei-Fei, and James Hays, Composing Text and Image for Image Retrieval-An Empirical Odyssey. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 [arXiv] [Code]
    • Chen Sun, Per Karlsson, Jiajun Wu, Joshua B. Tenenbaum, and Kevin Murphy, Stochastic Prediction of Multi-Agent Interactions from Partial Observations. International Conference on Learning Representations (ICLR) 2019 [arXiv] [Videos] [Annotations]
    • Zhenjia Xu*, Zhijian Liu*, Chen Sun, Kevin Murphy, William T. Freeman, Joshua B. Tenenbaum, and Jiajun Wu, Unsupervised Discovery of Parts, Structure, and Dynamics. International Conference on Learning Representations (ICLR) 2019 [arXiv] [Project] [Code]
    • Chen Sun, Fabien Baradel, Kevin Murphy, and Cordelia Schmid, Contrastive Bidirectional Transformer for Temporal Representation Learning. arXiv:1906.05743 [arXiv]
  • 2018

    • Chen Sun, Abhinav Shrivastava, Carl Vondrick, Kevin Murphy, Rahul Sukthankar and Cordelia Schmid, Actor-centric Relation Network. European Conference on Computer Vision (ECCV) 2018 [arXiv]
    • Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu and Kevin Murphy, Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification. European Conference on Computer Vision (ECCV) 2018 [arXiv] [Code] [Kinetics checkpoint] [HowTo100M checkpoint]
    • Chunhui Gu et al., AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 [arXiv] [Data] [Code]
    • Yin Cui, Yang Song, Chen Sun, Andrew Howard and Serge Belongie, Large Scale Fine-Grained Categorization and the Effectiveness of Domain-Specific Transfer Learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 [pdf] [Code]
    • Grant van Horn et al., The iNaturalist Species Classification and Detection Dataset. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 [pdf] [Data] [Detection baseline]
  • 2017

    • Chen Sun, Abhinav Shrivastava, Saurabh Singh and Abhinav Gupta, Revisiting Unreasonable Effectiveness of Data in Deep Learning Era. International Conference on Computer Vision (ICCV) 2017 [arXiv] [Blog] [WIRED]
    • Jonathan Huang et al., Speed/accuracy Trade-offs for Modern Convolutional Object Detectors. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 [arXiv] [Code]

Earlier Work

  • 2017
    • Jiyang Gao, Chen Sun, Zhenheng Yang and Ram Nevatia, TALL: Temporal Activity Localization via Language Query. International Conference on Computer Vision (ICCV) 2017 [arXiv] [Code]
    • Jiyang Gao*, Zhenheng Yang*, Chen Sun, Kan Chen and Ram Nevatia, TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals. International Conference on Computer Vision (ICCV) 2017 [arXiv] [Code]
    • Chuang Gan et al., VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation. International Conference on Computer Vision (ICCV) 2017 [pdf] [Data and code]
    • Chuang Gan*, Chen Sun* and Ram Nevatia, DECK: Discovering Event Composition Knowledge from Web Images for Zero-Shot Event Detection and Recounting in Videos. AAAI Conference on Artificial Intelligence (AAAI) 2017 [pdf]
  • 2016

    • Chen Sun, Manohar Paluri, Ronan Collobert, Ram Nevatia and Lubomir Bourdev, ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016 [arXiv]
    • Chuang Gan, Chen Sun, Lixin Duan and Boqing Gong, Webly-supervised video recognition by mutually voting for relevant web images and web video frames. European Conference on Computer Vision (ECCV) 2016 [pdf]
  • 2015

    • Chen Sun, Chuang Gan and Ram Nevatia, Automatic Concept Discovery from Parallel Text and Visual Corpora. International Conference on Computer Vision (ICCV) 2015 [arXiv]
    • Chen Sun, Sanketh Shetty, Rahul Sukthankar and Ram Nevatia, Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images. ACM Multimedia 2015 [arXiv]
  • 2014
    • Chen Sun, Ram Nevatia, Semantic Aware Video Transcription Using Random Forest Classifiers. European Conference on Computer Vision (ECCV) 2014 [pdf]
    • Chen Sun, Ram Nevatia, DISCOVER: Discovering Important Segments for Classification of Video Events and Recounting. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2014 [pdf]
    • Chen Sun, Brian Burns, Ram Nevatia, Cees Snoek, Bob Bolles, Greg Myers, Wen Wang, Eric Yeh, ISOMER: Informative Segment Observations for Multimedia Event Recounting. International Conference on Multimedia Retrieval (ICMR) 2014 [pdf]
    • Julien van Hout et al., Late Fusion and Calibration for Multimedia Event Detection Using Few Examples. International Conference on on Acoustics, Speech, and Signal Processing (ICASSP) 2014 [pdf]
  • 2013
    • Chen Sun, Ram Nevatia, ACTIVE: Activity Concept Transitions in Video Event Classification. International Conference on Computer Vision (ICCV) 2013 [pdf]
    • Chen Sun, Ram Nevatia, Large-scale Web Video Event Classification by use of Fisher Vectors. Workshop on Applications of Computer Vision (WACV) 2013 [pdf] [Code]