代季峰 - 清华大学 - 电子工程系

个人简介

Currently, I am an Associate Professor at Department of Electronic Engineering of Tsinghua University. My current research focus is on deep learning for high-level vision. Prior to that, I was an Executive Research Director at SenseTime Research, headed by Professor Xiaogang Wang, between 2019 and 2022. I was a Principle Research Manager in Visual Computing Group at Microsoft Research Asia (MSRA) between 2014 and 2019, headed by Dr. Jian Sun. I got my Ph.D. degree from the Department of Automation, Tsinghua University in 2014, under the supervison of Professor Jie Zhou. During my Ph.D. study, I visited the VCLA lab of University of California, Los Angeles (UCLA) between 2012 and 2013, where I worked with Professor Song-Chun Zhu and Professor Ying-Nian Wu. Before that, I got my B.S. degree from the Department of Automation, Tsinghua University in 2009, GPA ranking 2/160+.

研究领域

UniAD won the Best Paper Award of CVPR 2023 BEVFormer ranks 6th of the most influential papers in ECCV 2022 Deformable DETR ranks 2nd of the most influential papers in ICLR 2021 VL-BERT ranks 7th of the most influential papers in ICLR 2020 Deformable ConvNets ranks 6th of the most influential papers in ICCV 2017 R-FCN ranks 3rd of the most influential papers in NIPS 2016

近期论文

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The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World Weiyun Wang+, Min Shi*+, Qingyun Li*+, Wenhai Wang*+, Zhenhang Huang*+, Linjie Xing*+, Zhe Chen, Hao Li, Xizhou Zhu, Zhiguo Cao, Yushi Chen, Tong Lu, Jifeng Dai, Yu Qiao Arxiv Tech Report, 2023. Ghost in the Minecraft: Generally Capable Agents for Open-World Enviroments via Large Language Models with Text-based Knowledge and Memory Xizhou Zhu+, Yuntao Chen+, Hao Tian+, Chenxin Tao*+, Weijie Su*+, Chenyu Yang*+, Gao Huang, Bin Li, Lewei Lu, Xiaogang Wang, Yu Qiao, Zhaoxiang Zhang, Jifeng Dai Arxiv Tech Report, 2023. VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks Wenhai Wang+, Zhe Chen*+, Xiaokang Chen*+, Jiannan Wu*+, Xizhou Zhu, Gang Zeng, Ping Luo, Tong Lu, Jie Zhou, Yu Qiao, Jifeng Dai Arxiv Tech Report, 2023. Demystify Transformers & Convolutions in Modern Image Deep Networks Jifeng Dai+, Min Shi*+, Weiyun Wang*+, Sitong Wu*+, Linjie Xing, Wenhai Wang, Xizhou Zhu, Lewei Lu, Jie Zhou, Xiaogang Wang, Yu Qiao, Xiaowei Hu Arxiv Tech Report, 2022. Planning-oriented Autonomous Driving Yihan Hu+, Jiazhi Yang+, Li Chen+, Keyu Li, Chonghao Sima, Xizhou Zhu, Siqi Chai, Senyao Du, Tianwei Lin, Wenhai Wang, Lewei Lu, Xiaosong Jia, Qiang Liu, Jifeng Dai, Yu Qiao, Hongyang Li CVPR 2023. (CVPR Best Paper Award) BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision Chenyu Yang*+, Yuntao Chen+, Hao Tian+, Chenxin Tao*, Xizhou Zhu, Zhaoxiang Zhang, Gao Huang, Hongyang Li, Yu Qiao, Lewei Lu, Jie Zhou, Jifeng Dai CVPR 2023. (Highlight) Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information Weijie Su*+, Xizhou Zhu+, Chenxin Tao*+, Lewei Lu, Bin Li, Gao Huang, Yu Qiao, Xiaogang Wang, Jie Zhou, Jifeng Dai CVPR 2023. (Highlight) Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks Hao Li*+, Jingguo Zhu*+, Xiaohu Jiang*+, Xizhou Zhu, Hongsheng Li, Chun Yuan, Xiaohua Wang, Yu Qiao, Xiaogang Wang, Wenhai Wang, Jifeng Dai CVPR 2023. (Highlight) InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions Wenhai Wang+, Jifeng Dai+, Zhe Chen*+, Zhenhang Huang+, Zhiqi Li*+, Xizhou Zhu+, Xiaowei Hu, Tong Lu, Lewei Lu, Hongsheng Li, Xiaogang Wang, Yu Qiao CVPR 2023. (Highlight) Siamese Image Modeling for Self-Supervised Vision Representation Learning Chenxin Tao*+, Xizhou Zhu+, Gao Huang, Yu Qiao, Xiaogang Wang, Jifeng Dai CVPR 2023. (Highlight) Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs Jingguo Zhu*+, Xizhou Zhu+, Wenhai Wang, Xiaohua Wang, Hongsheng Li, Xiaogang Wang, Jifeng Dai NeurIPS, 2022. BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers Zhiqi Li*+, Wenhai Wang+, Hongyang Li+, Enze Xie, Chonghao Sima, Tong Lu, Qiao Yu, Jifeng Dai ECCV 2022. Code is available! BEVFormer won the 1-st place of Waymo 2022 3D Camera-Only Detection Task VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition Changyao Tian*+, Wenhai Wang+, Xizhou Zhu+, Xiaogang Wang, Jifeng Dai, Yu Qiao ECCV 2022. Exploring the Equivalence of Siamese Self-Supervised Learning via A Unified Gradient Framework Chenxin Tao*+, Honghui Wang*+, Xizhou Zhu+, Jiahua Dong, Shiji Song, Gao Huang, Jifeng Dai CVPR 2022. Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks Xizhou Zhu+, Jinguo Zhu*+, Hao Li*+, Xiaoshi Wu*+, Xiaogang Wang, Hongsheng Li, Xiaohua Wang, Jifeng Dai CVPR 2022. AutoLoss-Zero: Searching Loss Functions from Scratch for Generic Tasks Hao Li*+, Tianwen Fu*+, Jifeng Dai ,Hongsheng Li, Gao Huang, and Xizhou Zhu CVPR 2022. Searching Parameterized AP Loss for Object Detection Chenxin Tao*+, Zizhang Li*+, Xizhou Zhu+, Gao Huang, Yong Liu, Jifeng Dai NeurIPS 2021. Unsupervised Object Detection with LiDAR Clues Hao Tian*+, Yuntao Chen*+, Jifeng Dai , Zhaoxiang Zhang, and Xizhou Zhu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation Hao Li*+, Chenxin Tao*+, Xizhou Zhu, Xiaogang Wang, Gao Huang, and Jifeng Dai International Conference on Learning Representations (ICLR), 2021. Code is available! Deformable DETR: Deformable Transformers for End-to-End Object Detection Xizhou Zhu+, Weijie Su*+, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai International Conference on Learning Representations (ICLR), 2021.(Oral) Code is available! Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation Hang Gao*+, Xizhou Zhu*+, Steve Lin, and Jifeng Dai International Conference on Learning Representations (ICLR), 2020. VL-BERT: Pre-training of Generic Visual-Linguistic Representations Weijie Su*+, Xizhou Zhu*+, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai International Conference on Learning Representations (ICLR), 2020. Code is available! An Empirical Study of Spatial Attention Mechanisms in Deep Networks Xizhou Zhu*+, Dazhi Cheng*+, Zheng Zhang+, Steve Lin, and Jifeng Dai International Conference on Computer Vision (ICCV), 2019. Deformable ConvNets v2: More Deformable, Better Results Xizhou Zhu*, Han Hu, Steve Lin, and Jifeng Dai IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. The updated operators utilized in Deformable ConvNets v2 are provided here! Integrated Object Detection and Tracking with Tracklet-Conditioned Detection Zheng Zhang+, Dazhi Cheng*+, Xizhou Zhu*+, Steve Lin, and Jifeng Dai Arxiv Tech Report, 2018. Towards High Performance Video Object Detection for Mobiles Xizhou Zhu*, Jifeng Dai, Xingchi Zhu*, Yichen Wei, and Lu Yuan Arxiv Tech Report, 2018. Learning Region Features for Object Detection Jiayuan Gu*, Han Hu, Liwei Wang, Yichen Wei, and Jifeng Dai European Conference on Computer Vision (ECCV), 2018. Relation Networks for Object Detection Han Hu+, Jiayuan Gu*+, Zheng Zhang+, Jifeng Dai, and Yichen Wei IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. (Oral) Code is available! Towards High Performance Video Object Detection Xizhou Zhu*, Jifeng Dai, Lu Yuan, and Yichen Wei IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. (Spotlight) Deformable Convolutional Networks Jifeng Dai+, Haozhi Qi*+, Yuwen Xiong*+, Yi Li*+, Guodong Zhang*+, Han Hu, and Yichen Wei International Conference on Computer Vision (ICCV), 2017. (Oral) Code is available! Slides of ICCV Oral, COCO2017 workshop Flow-Guided Feature Aggregation for Video Object Detection Xizhou Zhu*, Yujie Wang*, Jifeng Dai, Lu Yuan, and Yichen Wei International Conference on Computer Vision (ICCV), 2017. Fully Convolutional Instance-aware Semantic Segmentation Yi Li*+, Haozhi Qi*+, Jifeng Dai, Xiangyang Ji, and Yichen Wei IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (Spotlight) 1-st place winner of the COCO 2016 segmentation challenge 0.24 sec/image test speed (using ResNet-101 net) Deep Feature Flow for Video Recognition Xizhou Zhu*, Yuwen Xiong*, Jifeng Dai, Lu Yuan, and Yichen Wei IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. Code is available! R-FCN: Object Detection via Region-based Fully Convolutional Networks Jifeng Dai, Yi Li, Kaiming He, and Jian Sun Neural Information Processing Systems (NIPS), 2016. Code is available! Instance-sensitive Fully Convolutional Networks Jifeng Dai, Kaiming He, Yi Li, Shaoqing Ren, and Jian Sun European Conference on Computer Vision (ECCV), 2016. ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation Di Lin*, Jifeng Dai, Jiaya Jia, Kaiming He, and Jian Sun IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (Oral) PASCAL-scribble dataset is available here! Instance-aware Semantic Segmentation via Multi-task Network Cascades Jifeng Dai, Kaiming He, and Jian Sun IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (Oral) 1-st place winner of the COCO 2015 segmentation challenge 0.36 sec/image test speed (using VGG-16 net) BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation Jifeng Dai, Kaiming He, and Jian Sun International Conference on Computer Vision (ICCV), 2015. Convolutional Feature Masking for Joint Object and Stuff Segmentation Jifeng Dai, Kaiming He, and Jian Sun IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. Generative Modeling of Convolutional Neural Networks Jifeng Dai, Yang Lu, and Ying-Nian Wu International Conference on Learning Representations (ICLR), 2015. Unsupervised Learning of Dictionaries of Hierarchical Compositional Models Jifeng Dai, Yi Hong, Wenze Hu, Song-Chun Zhu, and Ying-Nian Wu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. Cosegmentation and Cosketch by Unsupervised Learning Jifeng Dai, Ying-Nian Wu, Jie Zhou, and Song-Chun Zhu International Conference on Computer Vision (ICCV), 2013.\n\n Mining Sub-categories For Object Detection Jifeng Dai, Jianjiang Feng, and Jie Zhou International Conference on Pattern Recognition (ICPR), 2012. (Oral) Ridge Based Palmprint Matching Jifeng Dai, Jianjiang Feng, and Jie Zhou IEEE Biometrics Council Newsletter, 7:4-5, 2013. (Invited paper) Robust and Efficient Ridge-Based Palmprint Matching Jifeng Dai, Jianjiang Feng, and Jie Zhou IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 34(8):1618–1632, 2012. Multi-feature Based High-resolution Palmprint Recognition Jifeng Dai, and Jie Zhou IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 33(5):945–957, 2011.