Education

  • - PhD: Dept. of Electronic Engineering, Tsinghua University, August 2010 to January 2016
  • -Visiting student: Dept. of Electrical Engineering and Computer Science, Northwestern University, November 2014 to June 2015
  • -Bachelor: School of Information and Electronics, Beijing Institute of Technology, September 2006 to July 2010

Work Experience

  • -Tenure-track Associate Professor: Gaoling School of Artificial Intelligence, Renmin University of China, July 2020 to present
  • -Associate Professor: Institute of Software, Chinese Academy of Sciences, October 2018 to June 2020
  • - Assistant Professor: Institute of Software, Chinese Academy of Sciences, April 2016 to September 2018

RESEARCH INTERESTS

-Sequence distance learning: temporal alignment, metric learning for sequence data, dimensionality reduction for sequence data, optimal transport, temporal structure analysis

-Machine learning under restricted conditions: self-supervised learning, few-shot learning, zero-shot learning, transfer learning, federated learning, causal reasoning

-Computer vision: video classification, action recognition, visual and semantic correlation analysis, sequence prediction

PUBLICATIONS

2024
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)

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)

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 ({\bf 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.

Services

  • Associate Editor: Journal of Machine Vision and Applications, 2022−Present
  • Area Chair: CVPR 2024, NeurIPS 2023, CVPR 2023, MLSP 2021
  • Reviewer: IEEE TPAMI, IEEE TIP, IEEE TKDE, IEEE TCSVT
  • Reviewer: ICML, NeurIPS, CVPR, ICCV, ICLR, ECCV, ICME

Contact

Tel:

Email:bingsu@ruc.edu.cn; subingats@gmail.com

Website:

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