5 papers
CoLR-Det: Collaborative Latent Restoration for Small Object Detection in Low-Resolution Remote Sensing Images
Ruo Qi, Linhui Dai, Yusong Qin +2
Low-resolution remote sensing small object detection is limited by both missing visual details and the ambiguity of how details serve detection. Existing super-resolution-assisted…
EIVE: End-to-End Instance-Specific Visual Explanations for Detection Transformers
Jianlin Xiang, Yanshan Li, Linhui Dai
Visual explainability for object detection remains challenging due to the multi-instance nature of detection. Existing approaches predominantly adopt post-hoc paradigms, such as gr…
PIEDet: Prototype-Driven Intrinsically Explainable Object Detection
Jianlin Xiang, Linhui Dai, Xue Yang +2
Existing object detectors typically make predictions in a black-box manner and struggle to simultaneously provide discriminative evidence for their predictions, which limits their…
M3GCLR: Multi-View Mini-Max Infinite Skeleton-Data Game Contrastive Learning For Skeleton-Based Action Recognition
Yanshan Li, Ke Ma, Miaomiao Wei +1
In recent years, contrastive learning has drawn significant attention as an effective approach to reducing reliance on labeled data. However, existing methods for self-supervised s…
DoGCLR: Dominance-Game Contrastive Learning Network for Skeleton-Based Action Recognition
Yanshan Li, Ke Ma, Miaomiao Wei +1
Existing self-supervised contrastive learning methods for skeleton-based action recognition often process all skeleton regions uniformly, and adopt a first-in-first-out (FIFO) queu…