780 citations · 986 across the 36 of their papers we have counts for
9 papers · 1 filter
Chinese Character Recognition with Radical-Structured Stroke Trees
Haiyang Yu, Jingye Chen, Bin Li +1
The flourishing blossom of deep learning has witnessed the rapid development of Chinese character recognition. However, it remains a great challenge that the characters for testing…
Compositional Scene Modeling with Global Object-Centric Representations
Tonglin Chen, Bin Li, Zhimeng Shen +1
The appearance of the same object may vary in different scene images due to perspectives and occlusions between objects. Humans can easily identify the same object, even if occlusi…
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
Shangchao Su, Mingzhao Yang, Bin Li +1
Federated learning (FL) enables multiple clients to collaboratively train a global model without disclosing their data. Previous researches often require training the complete mode…
Domain Discrepancy Aware Distillation for Model Aggregation in Federated Learning
Shangchao Su, Bin Li, Xiangyang Xue
Knowledge distillation has recently become popular as a method of model aggregation on the server for federated learning. It is generally assumed that there are abundant public unl…
Compositional Law Parsing with Latent Random Functions
Fan Shi, Bin Li, Xiangyang Xue
Human cognition has compositionality. We understand a scene by decomposing the scene into different concepts (e.g., shape and position of an object) and learning the respective law…
Style Spectroscope: Improve Interpretability and Controllability through Fourier Analysis
Zhiyu Jin, Xuli Shen, Bin Li +1
Universal style transfer (UST) infuses styles from arbitrary reference images into content images. Existing methods, while enjoying many practical successes, are unable of explaini…
Cross-domain Federated Object Detection
Shangchao Su, Bin Li, Chengzhi Zhang +2
Detection models trained by one party (including server) may face severe performance degradation when distributed to other users (clients). Federated learning can enable multi-part…
One-shot Federated Learning without Server-side Training
Shangchao Su, Bin Li, Xiangyang Xue
Federated Learning (FL) has recently made significant progress as a new machine learning paradigm for privacy protection. Due to the high communication cost of traditional FL, one-…
Compositional Scene Representation Learning via Reconstruction: A Survey
Jinyang Yuan, Tonglin Chen, Bin Li +1
Visual scenes are composed of visual concepts and have the property of combinatorial explosion. An important reason for humans to efficiently learn from diverse visual scenes is th…