教育经历
2010年8月至2016年1月：清华大学，博士
2014年11月至2015年6月：美国西北大学，访问学生
2006年9月至2010年7月：北京理工大学，学士
工作经历
2023年8月-至今，中国人民大学高瓴人工智能学院，长聘副教授
2020年7月-2023年7月，中国人民大学高瓴人工智能学院，准聘副教授
2019年10月-2020年1月，微软亚洲研究院，铸星计划访问研究员
2018年10月-2020年6月，中国科学院软件研究所，副研究员
2016年4月-2018年9月，中国科学院软件研究所，助理研究员
研究方向
序列距离学习：时序对齐、距离学习、序列特征变换、时序结构建模
受限条件下的机器学习：自监督学习、多模态学习、迁移学习、因果推理、长尾分布
计算机视觉应用：视频分析、图像与视频生成/编辑、动作识别/分割/预测/生成、视觉与语义关联分析
自然科学中的序列数据建模与学习：分子/蛋白质/基因数据的表征学习、功能预测与生成
研究成果
学生要求
对研究有兴趣；具备一定的编程能力；踏实、勤奋。欢迎对我研究方向感兴趣的同学与我联系。
教授课程
人工智能与Python程序设计（本科生部类基础课）
人工智能综合设计（本科生科研与实践环节）
人工智能实践（研究生专业课）
科研项目
国家自然科学基金面上项目：基于时序约束的自监督序列表征学习方法研究（编号：62376277），主持
国家自然科学基金面上项目：基于最优传输的序列距离学习理论和方法研究（编号：61976206），主持
国家自然科学基金青年科学基金项目：基于最大化时序可分性的序列数据特征变换理论和方法研究（编号：61603373），主持
CCF腾讯犀牛鸟科研基金项目：自监督时序表征学习，主持
北京智源人工智能研究院悟道基金项目：基于多层级多视角限制的视觉表征预训练方法研究，主持
中国人民大学新教师启动金项目：基于时序对齐的序列距离度量与学习方法研究，主持
中国科学院青年创新促进会项目，主持
荣誉奖励
中国人民大学“杰出学者”青年学者，2020年
中科院软件所优秀科技人才计划，2019年
中国科学院青年创新促进会会员，2019年
社会兼职
Associate Editor：《Journal of Machine Vision and Applications》(MVA)（2022年至今）
Area Chair：CVPR 2024，NeurIPS 2023，CVPR 2023，MLSP 2021
期刊评审员：TPAMI，TIP，TKDE，TCSVT
会议评审员：ICML， NeurIPS，ICLR，CVPR，ICCV，ECCV，ICME
学术论文
2024
Instance-Specific Semantic Augmentation for Long-Tailed Image Classification
Jiahao Chen and Bing Su*
IEEE Transactions on Image Processing (TIP), 2024, (33): 2544 - 2557. (CCF A)
Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training
Jinxia Yang, Bing Su*, Xin Zhao*, and Ji-Rong Wen
International Conference on Machine Learning (ICML), accepted. (CCF A)
Dynamic Prompt Optimizing for Text-to-Image Generation
Wenyi Mo, Tianyu Zhang, Yalong Bai, Bing Su*, Ji-Rong Wen, and Qing Yang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, accepted. (CCF A)
Domain-adaptive and Subgroup-specific Cascaded Temperature Regression for Out-of-distribution Calibration
Jiexin Wang, Jiahao Chen, and Bing Su*
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, accepted. (CCF B)
Position-aware Active Learning for Multi-modal Entity Alignment
Baogui Xu, Yafei Lu, Bing Su, and Xiaoran Yan
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, accepted. (CCF B)
2023
Counterfactual Cross-modality Reasoning for Weakly Supervised Video Moment Localization
Zezhong Lv, Bing Su*, and Ji-Rong Wen
ACM International Conference on Multimedia (ACM MM), 2023, pp. 6539-6547. (CCF A)
Cross-Modal Graph Attention Network for Entity Alignment
Baogui Xu, Chengjin Xu, and Bing Su*
ACM International Conference on Multimedia (ACM MM), 2023, pp. 3715-3723. (CCF A)
Zero-shot Skeleton-based Action Recognition via Mutual Information Estimation and Maximization
Yujie Zhou, Wenwen Qiang, Anyi Rao, Ning Lin, Bing Su*, and Jiaqi Wang
ACM International Conference on Multimedia (ACM MM), 2023, pp. 5302-5310. (CCF A)
Synthesizing Long-Term Human Motions with Diffusion Models via Coherent Sampling
Zhao Yang, Bing Su*, and Ji-Rong Wen
ACM International Conference on Multimedia (ACM MM), 2023, pp. 3954-3964. (CCF A)
Task-sensitive Discriminative Mutual Attention Network for Few-shot Learning
Baogui Xu, Chengjin Xu, Zhiwu Lu, and Bing Su*
26th European Conference on Artificial Intelligence (ECAI), 2023, pp. 2784-2791. (CCF B)
Exploring Temporal Concurrency for Video-Language Representation Learning
Heng Zhang, Daqing Liu, Zezhong Lv, Bing Su*, and Dacheng Tao
IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 15568-15578. (CCF A)
Do we really need temporal convolutions in action segmentation?
Dazhao Du, Bing Su*, Yu Li, Zhongang Qi, Lingyu Si, and Ying Shan
IEEE International Conference on Multimedia and Expo (ICME), 2023, pp. 1014-1019. (CCF B)
Temporal-enhanced Cross-modality Fusion Network for Video Sentence Grounding
Zezhong Lv and Bing Su*
IEEE International Conference on Multimedia and Expo (ICME), 2023, pp. 1487-1492. (CCF B)
Transfer Knowledge from Head to Tail: Uncertainty Calibration under Long-tailed Distribution
Jiahao Chen and Bing Su*
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp. 19978-19987. (CCF A)
Modeling Video as Stochastic Processes for Fine-Grained Video Representation Learning
Heng Zhang, Daqing Liu, Qi Zheng, and Bing Su*
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp. 2225-2234. (CCF A)
Toward Auto-evaluation with Confidence-based Category Relation-aware Regression
Jiexin Wang, Jiahao Chen, and Bing Su*
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. (CCF B)
Decaying Contrast for Fine-grained Video Representation Learning
Heng Zhang and Bing Su*
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. (CCF B)
Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series Forecasting
Dazhao Du, Bing Su*, and Zhewei Wei
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. (CCF B)
Self-supervised Action Representation Learning from Partial Spatio-Temporal Skeleton Sequences
Yujie Zhou, Haodong Duan, Anyi Rao, Bing Su*, and Jiaqi Wang
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023, 37(3): 3825-3833. (CCF A)
Meta Attention-Generation Network for Cross-Granularity Few-Shot Learning
Wenwen Qiang, Jiangmeng Li, Bing Su*, Jianlong Fu, Hui Xiong, and Ji-Rong Wen
International Journal of Computer Vision (IJCV), 2023, 131: 1211–1233. (CCF A)
Discriminative Self-Paced Group-Metric Adaptation for Online Visual Identification
Jiahuan Zhou, Bing Su*, and Ying Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023, 45(4): 4368-4383. (CCF A)
Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity
Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su*, Farid Razzak, Ji-Rong Wen, and Hui Xiong
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 35(7): 7220-7238. (CCF A)
Robust Local Preserving and Global Aligning Network for Adversarial Domain Adaptation
Wenwen Qiang, Jiangmeng Li, Changwen Zheng, Bing Su*, and Hui Xiong
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 35(3): 3014-3029. (CCF A)
2022
MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning
Jiangmeng Li, Wenwen Qiang, Yanan Zhang, Wenyi Mo, Changwen Zheng, Bing Su*, and Hui Xiong
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022, pp. 38501--38515. (CCF A)
SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders
Gang Li, Heliang Zheng, Daqing Liu, Chaoyue Wang, Bing Su, and Changwen Zheng
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022, pp. 14290-14302. (CCF A)
Log-Polar Space Convolution Layers
Bing Su and Ji-Rong Wen
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022, pp. 5751-5765. (CCF A)
Convolutional Transformer with Similarity-based Boundary Prediction for Action Segmentation
Dazhao Du, Bing Su*, Yu Li, Zhongang Qi, Lingyu Si and Ying Shan
International Conference on Tool with Artificial Intelligence (ICTAI), short paper, 2022, pp. 855-860.
Optimal Partial Transport based Sentence Selection for Long-form Document Matching
Weijie Yu, Liang Pang, Jun Xu, Bing Su, Zhenhua Dong, and Ji-Rong Wen
International Conference on Computational Linguistics (COLING), 2022, pp. 2363–2373. (CCF B)
MetAug: Contrastive Learning via Meta Feature Augmentation
Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su*, and Hui Xiong
Proceedings of the 39th International Conference on Machine Learning (ICML), 2022. (CCF A)
Interventional Contrastive Learning with Meta Semantic Regularizer
Wenwen Qiang, Jiangmeng Li, Changwen Zheng, Bing Su*, and Hui Xiong
Proceedings of the 39th International Conference on Machine Learning (ICML), 2022. (CCF A)
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification
Bing Su and Ji-Rong Wen
International Conference on Learning Representations (ICLR), 2022
Linear and Deep Order-Preserving Wasserstein Discriminant Analysis
Bing Su, Jiahuan Zhou, Ji-Rong Wen, and Ying Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022, 44(6): 3123-3138. (CCF A)
Learning Meta-Distance for Sequences by Learning a Ground Metric via Virtual Sequence Regression
Bing Su* and Ying Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022, 44(1): 286-301. (CCF A)
Transductive Distribution Calibration for Few-shot Learning
Gang Li, Changwen Zheng, and Bing Su*
Neurocomputing, 2022, 500: 604-615
RHMC: Modeling consistent information from deep multiple views via Regularized and Hybrid Multiview Coding
Jiangmeng Li, Wenwen Qiang, Changwen Zheng, and Bing Su*
Knowledge-Based Systems (KBS), 2022, 241: 108201.
Monocular contextual constraint for stereo matching with adaptive weights assignment
Chenghao Zhang, Gaofeng Meng, Bing Su, Shiming Xiang, and Chunhong Pan
Image and Vision Computing, 2022, 121: 104424
2021
Auxiliary task guided mean and covariance alignment network for adversarial domain adaptation
Wenwen Qiang, Jiangmeng Li, Changwen Zheng, and Bing Su*
Knowledge-Based Systems (KBS), 2021, 223: 107066.
2020
Online Joint Multi-Metric Adaptation from Frequent Sharing-Subset Mining for Person Re-Identification
Jiahuan Zhou, Bing Su, and Ying Wu,
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (CCF A)
Learning Low-Dimensional Temporal Representations with Latent Alignments
Bing Su* and Ying Wu
IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2020, 42(11): 2842-2857. (CCF A)
2019
Learning Distance for Sequences by Learning a Ground Metric
Bing Su* and Ying Wu
International Conference on Machine Learning (ICML), 2019, pp. 6015-6025. (CCF A)
Order-Preserving Wasserstein Discriminant Analysis
Bing Su*, Jiahuan Zhou, and Ying Wu
IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 9885-9894. (CCF A)
Order-preserving Optimal Transport for Distances between Sequences
Bing Su* and Gang Hua
IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2019, 41(12), pp. 2961-2974. (CCF A)
2018
Spatiotemporal Pyramid Pooling in 3D Convolutional Neural Networks for Action Recognition
Cheng Cheng, Pin Lv, and Bing Su
IEEE International Conference on Image Processing (ICIP), 2018, pp. 3468-3472.
Feature Fusion Network for Scene Text Detection
Chenqin Cai, Pin Lv, and Bing Su
IEEE International Conference on Image Processing (ICIP), 2018, pp. 2755-2759.
Easy Identification from Better Constraints: Multi-Shot Person Re-Identification from Reference Constraints
Jiahuan Zhou, Bing Su, and Ying Wu
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2018, pp. 5373-5381. (CCF A)
Learning Low-Dimensional Temporal Representations
Bing Su* and Ying Wu
International Conference on Machine Learning (ICML), 2018, pp. 4761-4770. (CCF A)
Discriminative Dimensionality Reduction for Multi-Dimensional Sequences
Bing Su*, Xiaoqing Ding, Hao Wang, and Ying Wu
IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2018, 40(1), pp. 77-91. (CCF A)
Heteroscedastic Max–Min Distance Analysis for Dimensionality Reduction
Bing Su*, Xiaoqing Ding, Changsong Liu, and Ying Wu
IEEE Trans. on Image Processing (TIP), 2018, 27(8), pp. 4052-4065. (CCF A)
2017
Order-preserving Wasserstein Distance for Sequence Matching
Bing Su* and Gang Hua
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 1049-1057. (CCF A)
Discriminative Transformation for Multi-dimensional Temporal Sequences
Bing Su*, Xiaoqing Ding, Changsong Liu, Hao Wang, and Ying Wu
IEEE Trans. on Image Processing (TIP), 2017, 26(7), pp. 3579-3593. (CCF A)
Unsupervised Hierarchical Dynamic Parsing and Encoding for Action Recognition
Bing Su*, Jiahuan Zhou, Xiaoqing Ding, and Ying Wu
IEEE Trans. on Image Processing (TIP), 2017, 26(12), pp. 5784-5799. (CCF A)
2016
Hierarchical Dynamic Parsing and Encoding for Action Recognition
Bing Su*, Jiahuan Zhou, Xiaoqing Ding, Hao Wang, and Ying Wu
Proc. European Conf. on Computer Vision (ECCV), 2016, pp. 202-217. (CCF B)
2015
Heteroscedastic Max-Min Distance Analysis
Bing Su*, Xiaoqing Ding, Changsong Liu, and Ying Wu
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 4539-4547. (CCF A)
2013
A Novel Baseline-independent Feature Set for Arabic Handwriting Recognition
Bing Su*, Xiaoqing Ding, Liangrui Peng, and Changsong Liu
International Conference on Document Analysis and Recognition (ICDAR), 2013, pp. 1282-1286.
Cross-language Sensitive Words Distribution Map: A Novel Recognition-based Document Understanding Method for Uighur and Tibetan
Bing Su*, Xiaoqing Ding, Liangrui Peng, and Changsong Liu
International Conference on Document Analysis and Recognition (ICDAR), 2013, pp. 255-259.
Linear Sequence Discriminant Analysis: A Model-Based Dimensionality Reduction Method for Vector Sequences
Bing Su* and Xiaoqing Ding
IEEE International Conference on Computer Vision (ICCV), 2013, pp. 889–896. (CCF A)
2011
SemiBoost-based Arabic character recognition method
Bing Su, Liangrui Peng, and Xiaoqing Ding
Proc. SPIE 7874, Document Recognition and Retrieval XVIII (SPIE DRR), 2011.
