Bin Li - AImpressionist
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Bin Li
Email: libin AT fudan DOT edu DOT cn |
Biography
I'm an associate professor of computer science at Fudan University since Nov 2017. Prior to this, I was a research fellow at Institut TELECOM SudParis from 2009 to 2010, a lecturer at University of Technology Sydney (UTS) from 2011 to 2013, and a senior research scientist of machine learning at CSIRO's Data61 (formerly NICTA) from 2013 to 2017. I received my PhD degree in computer science from Fudan University in 2009. My current research interests lie in machine learning, visual intelligence, and data science, particularly in complex data (e.g., relational, structured, and streaming) representation, modeling and inference.
News
I am seeking PhD students interested in foundational problems at the intersection of deep latent variable models and visual intelligence.
2023-06: A real-world dataset of tabletop scenes OCTScenes for benchmarking Object-Centric Learning is released online.
2023-06: Compositional Scene Representation Learning via Reconstruction: A Survey is published online at IEEE TPAMI.
2022-06: A survey with a toolbox for Compositional Scene Representation Learning is released online.
2022-01: A report with a data collection for benchmarking Chinese text recognition is released online.
2021-05: A software package Dr.Hash -- Data Representation with Hashing Toolbox is released online.
2021-04: Bayesian Nonparametric Space Partitions: A Survey is published at IJCAI-21 Survey Track.
2021-01: A software package Sparti -- Spatial Partition Inference Toolbox is released online.
2020-09: A Review for Weighted MinHash Algorithms is published online at IEEE TKDE.
Research
Some selected research topics are listed below. The full list of my publication can be found here.
Scene Text Recognition, Segmentation and Super-Resolution
Haiyang Yu, Jingye Chen, Bin Li, Xiangyang Xue, Chinese Character Recognition with Radical-Structured Stroke Trees, MLJ. [code]
Xinyan Zu, Haiyang Yu, Bin Li, Xiangyang Xue, Weakly-Supervised Text Instance Segmentation, MM-23. [code]
Haiyang Yu, Xiaocong Wang, Ke Niu, Bin Li, Xiangyang Xue, Scene Text Segmentation with Text-Focused Transformers, MM-23. [code]
Haiyang Yu, Xiaocong Wang, Bin Li, Xiangyang Xue, Chinese Text Recognition with A Pre-Trained CLIP-Like Model Through Image-IDS Aligning, ICCV-23. [code]
Haiyang Yu, Xiaocong Wang, Bin Li, Xiangyang Xue, Orientation-Independent Chinese Text Recognition in Scene Images, IJCAI-23. [code]
Xinyan Zu, Haiyang Yu, Bin Li, Xiangyang Xue, Towards Accurate Video Text Spotting with Text-wise Semantic Reasoning, IJCAI-23. [code]
Xinyan Zu, Haiyang Yu, Bin Li, Xiangyang Xue, Chinese Character Recognition with Augmented Character Profile Matching, MM-22. [code]
Jingye Chen, Haiyang Yu, Jianqi Ma, Bin Li, Xiangyang Xue, Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution, AAAI-22. [code]
Jingye Chen, Bin Li, Xiangyang Xue, Zero-Shot Chinese Character Recognition with Stroke-Level Decomposition, IJCAI-21. [code]
Jingye Chen, Bin Li, Xiangyang Xue, Scene Text Telescope: Text-Focused Scene Image Super-Resolution, CVPR-21. [code]
Compositional Scene Modeling and Object-Centric Learning
Fan Shi, Bin Li, Xiangyang Xue, Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection, ICLR-24. [code]
Jinyang Yuan, Tonglin Chen, Zhimeng Shen, Bin Li, Xiangyang Xue, Unsupervised Object-Centric Learning from Multiple Unspecified Viewpoints, IEEE TPAMI, 2024. [code]
Tonglin Chen, Zhimeng Shen, Bin Li, Xiangyang Xue, Compositional Scene Modeling with Global Object-Centric Representations, MLJ. [code]
Zhiyu Jin, Xuli Shen, Bin Li, Xiangyang Xue, Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesis, NeurIPS-23. [code]
Jinyang Yuan, Tonglin Chen, Bin Li, Xiangyang Xue, Compositional Scene Representation Learning via Reconstruction: A Survey, IEEE TPAMI, 2023. [code]
Chengmin Gao, Bin Li, Time-Conditioned Generative Modeling of Object-Centric Representations for Video Decomposition and Prediction, UAI-23. [code]
Fan Shi, Bin Li, Xiangyang Xue, Compositional Law Parsing with Latent Random Functions, ICLR-23. [code]
Jinyang Yuan, Bin Li, Xiangyang Xue, Unsupervised Learning of Compositional Scene Representations from Multiple Unspecified Viewpoints, AAAI-22. [code]
Jinyang Yuan, Bin Li, Xiangyang Xue, Knowledge-Guided Object Discovery with Acquired Deep Impressions, AAAI-21. [code]
Fan Shi, Bin Li, Xiangyang Xue, Raven's Progressive Matrices Completion with Latent Gaussian Process Priors, AAAI-21. [code]
Jinyang Yuan, Bin Li, Xiangyang Xue, Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation, ICML-19. [code]
Jinyang Yuan, Bin Li, Xiangyang Xue, Spatial Mixture Models with Learnable Deep Priors for Perceptual Grouping, AAAI-19. [code]
Stochastic Partitions and Stochastic Point Processes
Xuhui Fan, Yaqiong Li, Ling Chen, Bin Li, Scott A. Sisson, Hawkes Processes with Stochastic Exogenous Effects for Continuous-Time Interaction Modelling, IEEE TPAMI, 2023. [code]
Xuhui Fan, Bin Li, Feng Zhou, Scott A. Sisson, Continuous-Time Edge Modelling using Non-Parametric Point Processes, NeurIPS-21. [code]
Xuhui Fan, Bin Li, Yaqiong Li, Scott A. Sisson, Poisson-Randomised DirBNs: Large Mutation is Needed in Dirichlet Belief Networks, ICML-21. [code]
Xuhui Fan, Bin Li, Ling Luo, Scott A. Sisson, Bayesian Nonparametric Space Partitions: A Survey, IJCAI-21. [code]
Xuhui Fan, Bin Li, Scott A. Sisson, Online Binary Space Partitioning Forests, AISTATS-20. [code]
Xuhui Fan, Bin Li, Scott A. Sisson, Caoyuan Li, Ling Chen, Scalable Deep Generative Relational Models with High-Order Node Dependence, NeurIPS-19. [code]
Xuhui Fan, Bin Li, Scott A. Sisson, Binary Space Partitioning Forests, AISTATS-19. [code]
Xuhui Fan, Bin Li, Scott A. Sisson, Rectangular Bounding Process, NeurIPS-18. [code]
Xuhui Fan, Bin Li, Scott A. Sisson. The Binary Space Partitioning-Tree process, AISTATS-18. [code]
Xuhui Fan, Bin Li, Yi Wang, Yang Wang, Fang Chen, The Ostomachion Process, AAAI-16.
Yi Wang, Bin Li, Xuhui Fan, Yang Wang, Fang Chen, Bayesian Optimization of Partition Layouts for Mondrian Processes, IJCAI-16.
Yi Wang, Bin Li, Yang Wang, Fang Chen, Metadata Dependent Mondrian Processes, ICML-15.
Structured Data Representation with Recursive Hashing
Wei Wu, Bin Li, Chuan Luo, Wolfgang Nejdl, Xuan Tan, MPSketch: Message Passing Networks via Randomized Hashing for Efficient Attributed Network Embedding, IEEE TCYB, 2023. [code]
Wei Wu, Bin Li, Ling Chen, Junbin Gao, Chengqi Zhang, A Review for Weighted MinHash Algorithms, IEEE TKDE, 2022. [code]
Wei Wu, Bin Li, Chuan Luo, Wolfgang Nejdl, Hashing-Accelerated Graph Neural Networks for Link Prediction, WWW-21. [code]
Dingqi Yang, Paolo Rosso, Bin Li, Philippe Cudré-Mauroux, NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching, KDD-19.
Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Philip S. Yu, Improved Consistent Weighted Sampling Revisited, IEEE TKDE, 2019. [code]
Dingqi Yang, Bin Li, Laura Rettig, Philippe Cudré-Mauroux, D2HistoSketch: Discriminative and Dynamic Similarity-Preserving Sketching of Streaming Histograms, IEEE TKDE, 2019.
Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Efficient Attributed Network Embedding via Recursive Randomized Hashing, IJCAI-18. [code]
Wei Wu, Bin Li, Ling Chen, Ling Chen, Xingquan Zhu, Chengqi Zhang, $K$-Ary Tree Hashing for Fast Graph Classification, IEEE TKDE, 2018. [code]
Dingqi Yang, Bin Li, Laura Rettig, Philippe Cudré-Mauroux, HistoSketch: Fast Similarity-Preserving Sketching of Streaming Histograms with Concept Drift, ICDM-17.
Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Consistent Weighted Sampling Made More Practical, WWW-17. [code]
Dingqi Yang, Bin Li, Philippe Cudré-Mauroux, POIsketch: Semantic Place Labeling over User Activity Streams, IJCAI-16.
Lianhua Chi, Bin Li, Xingquan Zhu, Context-Preserving Hashing for Fast Text Classification, SDM-14.
Bin Li, Xingquan Zhu, Lianhua Chi, Chengqi Zhang, Nested Subtree Hash Kernels for Large-scale Graph Classification over Streams, ICDM-12.
Collaborative Filtering and User Behaviour Modeling
Ling Luo, Bin Li, Xuhui Fan, Yang Wang, Irena Koprinska, Fang Chen, Dynamic Customer Segmentation via Hierarchical Fragmentation-Coagulation Processes, MLJ, 2023.
Ling Luo, Bin Li, Irena Koprinska, Shlomo Berkovsky, Fang Chen, Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process, IJCAI-17.
Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Rating Knowledge Sharing in Cross-Domain Collaborative Filtering, IEEE TCYB, 2015.
Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, XindongWu, Cross-Domain Collaborative Filtering over Time, IJCAI-11.
Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, Xingquan Zhu, Tracking User-Preference Varying Speed in Collaborative Filtering, AAAI-11.
Bin Li, Qiang Yang, Xiangyang Xue, Transfer Learning for Collaborative Filtering via a Rating-Matrix Generative Model, ICML-09.
Bin Li, Qiang Yang, Xiangyang Xue, Can Movies and Books Collaborate? Cross-Domain Collaborative Filtering for Sparsity Reduction, IJCAI-09.
Team
Some of my students and team alumni are listed below. I was external PhD supervisor at UTS, USyd and UNSW when I worked for NICTA/CSIRO in Australia.
Research Students
Haiyang Yu (PhD'22/MEng'20 Student@Fudan) supervised 2020~Now.
Fan Shi (PhD'22/MSc'19 Student@Fudan) supervised 2019~Now.
Mingzhao Yang (PhD'20/MSc'18 Student@Fudan) supervised 2020~Now.
Shangchao Su (PhD'20/MSc'18 Student@Fudan) supervised 2018~Now.
Tonglin Chen (PhD'18 Student@Fudan) supervised 2018~Now.
Team Alumni
Xinyan Zu (MEng@Fudan) supervised 2020~2023 on Chinese Text Recognition. Shanghai Computer Society Outstanding Theses Award
Jinyang Yuan (PhD@Fudan) co-supervised 2018~2022 on Compositional Scene Modeling.
Jingye Chen (MEng@Fudan) supervised 2019~2022 on Scene Text Recognition. Shanghai Computer Society Outstanding Theses Award
Yaqiong Li (PhD@UTS) co-supervised 2017~2021 on Bayesian Dynamic Network Modeling.
Wei Wu (PhD@UTS) co-supervised 2015~2018 on Structured Data Hashing.
Ling Luo (PhD@USyd) co-supervised 2015~2017 on Temporal Behavior Modeling. Google PhD Fellowship | Springer Theses
Xuhui Fan (Postdoc@CSIRO) supervised 2015~2017 on Bayesian Nonparametric Space Partitions.
Yi Wang (PhD@UNSW) co-supervised 2014~2016 on Bayesian Nonparametric Clustering.
Lianhua Chi (PhD@UTS) co-supervised 2012~2015 on Structured Data Hashing.
Ruijiang Li (PhD@Fudan) co-supervised 2009~2013 on Bayesian Subspace Clustering.
Teaching
Mathematical Foundations of Artificial Intelligence (Undergraduate): 2023Fall
Statistical Learning (Undergraduate): 2020Fall, 2021Fall, 2022Fall, 2023Fall
Big Data Analytics and Applications (Graduate): 2018Fall, 2019Fall, 2020Fall, 2021Fall, 2022Fall, 2024Spring
Software
