Kang, Bingyi

34 publications

ICLR 2026 Depth Anything 3: Recovering the Visual Space from Any Views Haotong Lin, Sili Chen, Jun Hao Liew, Donny Y. Chen, Zhenyu Li, Yang Zhao, Sida Peng, Hengkai Guo, Xiaowei Zhou, Guang Shi, Jiashi Feng, Bingyi Kang

ICLR 2026 Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots Minghuan Liu, Zhengbang Zhu, Xiaoshen Han, PengHu, Haotong Lin, Xinyao Li, Jingxiao Chen, Jiafeng Xu, Yichu Yang, Yunfeng Lin, Xinghang Li, Yong Yu, Weinan Zhang, Tao Kong, Bingyi Kang

ICLR 2026 Trace Anything: Representing Any Video in 4D via Trajectory Fields Xinhang Liu, Yuxi Xiao, Donny Y. Chen, Jiashi Feng, Yu-Wing Tai, Chi-Keung Tang, Bingyi Kang

ICML 2025 How Far Is Video Generation from World Model: A Physical Law Perspective Bingyi Kang, Yang Yue, Rui Lu, Zhijie Lin, Yang Zhao, Kaixin Wang, Gao Huang, Jiashi Feng

CVPR 2025 Prompting Depth Anything for 4k Resolution Accurate Metric Depth Estimation Haotong Lin, Sida Peng, Jingxiao Chen, Songyou Peng, Jiaming Sun, Minghuan Liu, Hujun Bao, Jiashi Feng, Xiaowei Zhou, Bingyi Kang

ICCV 2025 SpatialTrackerV2: Advancing 3D Point Tracking with Explicit Camera Motion Yuxi Xiao, Jianyuan Wang, Nan Xue, Nikita Karaev, Yuri Makarov, Bingyi Kang, Xing Zhu, Hujun Bao, Yujun Shen, Xiaowei Zhou

CVPR 2025 Video Depth Anything: Consistent Depth Estimation for Super-Long Videos Sili Chen, Hengkai Guo, Shengnan Zhu, Feihu Zhang, Zilong Huang, Jiashi Feng, Bingyi Kang

CVPR 2025 VideoWorld: Exploring Knowledge Learning from Unlabeled Videos Zhongwei Ren, Yunchao Wei, Xun Guo, Yao Zhao, Bingyi Kang, Jiashi Feng, Xiaojie Jin

NeurIPS 2024 Classification Done Right for Vision-Language Pre-Training Zilong Huang, Qinghao Ye, Bingyi Kang, Jiashi Feng, Haoqi Fan

NeurIPS 2024 DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution Yang Yue, Yulin Wang, Bingyi Kang, Yizeng Han, Shenzhi Wang, Shiji Song, Jiashi Feng, Gao Huang

NeurIPS 2024 Depth Anything V2 Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao

CVPR 2024 Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao

NeurIPS 2024 Image Understanding Makes for a Good Tokenizer for Image Generation Luting Wang, Yang Zhao, Zijian Zhang, Jiashi Feng, Si Liu, Bingyi Kang

ICML 2024 Improving Token-Based World Models with Parallel Observation Prediction Lior Cohen, Kaixin Wang, Bingyi Kang, Shie Mannor

NeurIPS 2024 MADiff: Offline Multi-Agent Learning with Diffusion Models Zhengbang Zhu, Minghuan Liu, Liyuan Mao, Bingyi Kang, Minkai Xu, Yong Yu, Stefano Ermon, Weinan Zhang

ICML 2023 Bag of Tricks for Training Data Extraction from Language Models Weichen Yu, Tianyu Pang, Qian Liu, Chao Du, Bingyi Kang, Yan Huang, Min Lin, Shuicheng Yan

NeurIPS 2023 Efficient Diffusion Policies for Offline Reinforcement Learning Bingyi Kang, Xiao Ma, Chao Du, Tianyu Pang, Shuicheng Yan

NeurIPS 2023 FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models Lihe Yang, Xiaogang Xu, Bingyi Kang, Yinghuan Shi, Hengshuang Zhao

NeurIPS 2023 Mutual Information Regularized Offline Reinforcement Learning Xiao Ma, Bingyi Kang, Zhongwen Xu, Min Lin, Shuicheng Yan

ICLR 2023 Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments Kaixin Wang, Kuangqi Zhou, Bingyi Kang, Jiashi Feng, Shuicheng Yan

NeurIPS 2023 Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL Yang Yue, Rui Lu, Bingyi Kang, Shiji Song, Gao Huang

AAAI 2023 Value-Consistent Representation Learning for Data-Efficient Reinforcement Learning Yang Yue, Bingyi Kang, Zhongwen Xu, Gao Huang, Shuicheng Yan

NeurIPSW 2022 Boosting Offline Reinforcement Learning via Data Rebalancing Yang Yue, Bingyi Kang, Xiao Ma, Zhongwen Xu, Gao Huang, Shuicheng Yan

NeurIPSW 2022 Mutual Information Regularized Offline Reinforcement Learning Xiao Ma, Bingyi Kang, Zhongwen Xu, Min Lin, Shuicheng Yan

ICLR 2021 Exploring Balanced Feature Spaces for Representation Learning Bingyi Kang, Yu Li, Sa Xie, Zehuan Yuan, Jiashi Feng

ICLR 2021 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control Zhuang Liu, Xuanlin Li, Bingyi Kang, Trevor Darrell

ICLR 2020 Decoupling Representation and Classifier for Long-Tailed Recognition Bingyi Kang, Saining Xie, Marcus Rohrbach, Zhicheng Yan, Albert Gordo, Jiashi Feng, Yannis Kalantidis

NeurIPS 2020 Improving Generalization in Reinforcement Learning with Mixture Regularization Kaixin Wang, Bingyi Kang, Jie Shao, Jiashi Feng

CVPR 2020 Overcoming Classifier Imbalance for Long-Tail Object Detection with Balanced Group SoftMax Yu Li, Tao Wang, Bingyi Kang, Sheng Tang, Chunfeng Wang, Jintao Li, Jiashi Feng

ECCV 2020 The Devil Is in Classification: A Simple Framework for Long-Tail Instance Segmentation Tao Wang, Yu Li, Bingyi Kang, Junnan Li, Junhao Liew, Sheng Tang, Steven Hoi, Jiashi Feng

ICCV 2019 Few-Shot Object Detection via Feature Reweighting Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell

ICML 2018 Policy Optimization with Demonstrations Bingyi Kang, Zequn Jie, Jiashi Feng

IJCAI 2018 Sharing Residual Units Through Collective Tensor Factorization to Improve Deep Neural Networks Yunpeng Chen, Xiaojie Jin, Bingyi Kang, Jiashi Feng, Shuicheng Yan

UAI 2018 Transferable Meta Learning Across Domains Bingyi Kang, Jiashi Feng