26 citations · 41 across the 20 of their papers we have counts for
6 papers · 1 filter
Chairs Can be Stood on: Overcoming Object Bias in Human-Object Interaction Detection
Guangzhi Wang, Yangyang Guo, Yongkang Wong +1
Detecting Human-Object Interaction (HOI) in images is an important step towards high-level visual comprehension. Existing work often shed light on improving either human and object…
A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQA
Yangyang Guo, Liqiang Nie, Yongkang Wong +3
Knowledge-based Visual Question Answering (VQA) expects models to rely on external knowledge for robust answer prediction. Though significant it is, this paper discovers several le…
Voice-Face Homogeneity Tells Deepfake
Harry Cheng, Yangyang Guo, Tianyi Wang +3
Detecting forgery videos is highly desirable due to the abuse of deepfake. Existing detection approaches contribute to exploring the specific artifacts in deepfake videos and fit w…
MERIt: Meta-Path Guided Contrastive Learning for Logical Reasoning
Fangkai Jiao, Yangyang Guo, Xuemeng Song +1
Logical reasoning is of vital importance to natural language understanding. Previous studies either employ graph-based models to incorporate prior knowledge about logical relations…
On Modality Bias Recognition and Reduction
Yangyang Guo, Liqiang Nie, Harry Cheng +3
Making each modality in multi-modal data contribute is of vital importance to learning a versatile multi-modal model. Existing methods, however, are often dominated by one or few o…
Joint Answering and Explanation for Visual Commonsense Reasoning
Zhenyang Li, Yangyang Guo, Kejie Wang +3
Visual Commonsense Reasoning (VCR), deemed as one challenging extension of the Visual Question Answering (VQA), endeavors to pursue a more high-level visual comprehension. It is co…