视频简介

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

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

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)
链接: 链接

Spatio-Temporal Branching for Motion Prediction using Motion Increments
Jiexin Wang, Yujie Zhou, Wenwen Qiang, Ying Ba, Bing Su*, and Ji-Rong Wen
ACM International Conference on Multimedia (ACM MM), 2023, pp. 4290-4299. (CCF A)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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.
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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
链接: 链接

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)
链接: 链接

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)
链接: 链接

Transductive Distribution Calibration for Few-shot Learning
Gang Li, Changwen Zheng, and Bing Su*
Neurocomputing, 2022, 500: 604-615
链接: 链接

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.
链接: 链接

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
链接: 链接

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.
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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)
链接: 链接

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.

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

contact

电话:--

邮箱:bingsu@ruc.edu.cn

个人网页:--

办公地址:中国人民大学立德楼1721