74 citations · 98 across the 7 of their papers we have counts for
8 papers
No More Sibling Rivalry: Debiasing Human-Object Interaction Detection
Bin Yang, Yulin Zhang, Hong-Yu Zhou +1
Detection transformers have been applied to human-object interaction (HOI) detection, enhancing the localization and recognition of human-action-object triplets in images. Despite…
MAC: A Benchmark for Multiple Attributes Compositional Zero-Shot Learning
Shuo Xu, Sai Wang, Xinyue Hu +3
Compositional Zero-Shot Learning (CZSL) aims to learn semantic primitives (attributes and objects) from seen compositions and recognize unseen attribute-object compositions. Existi…
DDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models
Ge Zheng, Bin Yang, Jiajin Tang +2
A long-standing goal of AI systems is to perform complex multimodal reasoning like humans. Recently, large language models (LLMs) have made remarkable strides in such multi-step re…
TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition
Meng Lou, Shu Zhang, Hong-Yu Zhou +3
Recent studies have integrated convolutions into transformers to introduce inductive bias and improve generalization performance. However, the static nature of conventional convolu…
PCRLv2: A Unified Visual Information Preservation Framework for Self-supervised Pre-training in Medical Image Analysis
Hong-Yu Zhou, Chixiang Lu, Chaoqi Chen +2
Recent advances in self-supervised learning (SSL) in computer vision are primarily comparative, whose goal is to preserve invariant and discriminative semantics in latent represent…
Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse Contexts
Hong-Yu Zhou, Chixiang Lu, Sibei Yang +2
Preserving maximal information is one of principles of designing self-supervised learning methodologies. To reach this goal, contrastive learning adopts an implicit way which is co…