109 citations · 236 across the 12 of their papers we have counts for
12 papers
Your Negative May not Be True Negative: Boosting Image-Text Matching with False Negative Elimination
Haoxuan Li, Yi Bin, Junrong Liao +2
Most existing image-text matching methods adopt triplet loss as the optimization objective, and choosing a proper negative sample for the triplet of <anchor, positive, negative> is…
Unifying Two-Stream Encoders with Transformers for Cross-Modal Retrieval
Yi Bin, Haoxuan Li, Yahui Xu +3
Most existing cross-modal retrieval methods employ two-stream encoders with different architectures for images and texts, \textit{e.g.}, CNN for images and RNN/Transformer for text…
Faster Video Moment Retrieval with Point-Level Supervision
Xun Jiang, Zailei Zhou, Xing Xu +3
Video Moment Retrieval (VMR) aims at retrieving the most relevant events from an untrimmed video with natural language queries. Existing VMR methods suffer from two defects: (1) ma…
Non-Autoregressive Math Word Problem Solver with Unified Tree Structure
Yi Bin, Mengqun Han, Wenhao Shi +4
Existing MWP solvers employ sequence or binary tree to present the solution expression and decode it from given problem description. However, such structures fail to handle the var…
Learning Semantic-Aware Knowledge Guidance for Low-Light Image Enhancement
Yuhui Wu, Chen Pan, Guoqing Wang +4
Low-light image enhancement (LLIE) investigates how to improve illumination and produce normal-light images. The majority of existing methods improve low-light images via a global…
A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?
Chaoning Zhang, Chenshuang Zhang, Sheng Zheng +14
As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. With su…