12 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CV2026
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…
cs.CV2026★ 12 cited
Dual-stream Spatio-Temporal GCN-Transformer Network for 3D Human Pose Estimation
Jiawen Duan, Jian Xiang, Zhiqiang Li +2
3D human pose estimation is a classic and important research direction in the field of computer vision. In recent years, Transformer-based methods have made significant progress in…
cs.CV2026
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…