6 citations · 13 across the 6 of their papers we have counts for
6 papers
Uncertainty-aware Unsupervised Multi-Object Tracking
Kai Liu, Sheng Jin, Zhihang Fu +3
Without manually annotated identities, unsupervised multi-object trackers are inferior to learning reliable feature embeddings. It causes the similarity-based inter-frame associati…
Spatial Likelihood Voting with Self-Knowledge Distillation for Weakly Supervised Object Detection
Ze Chen, Zhihang Fu, Jianqiang Huang +5
Weakly supervised object detection (WSOD), which is an effective way to train an object detection model using only image-level annotations, has attracted considerable attention fro…
Dynamic Supervisor for Cross-dataset Object Detection
Ze Chen, Zhihang Fu, Jianqiang Huang +6
The application of cross-dataset training in object detection tasks is complicated because the inconsistency in the category range across datasets transforms fully supervised learn…
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware Association
Sen Yang, Zhicheng Wang, Ze Chen +7
This paper presents a new method to solve keypoint detection and instance association by using Transformer. For bottom-up multi-person pose estimation models, they need to detect k…
Guiding Query Position and Performing Similar Attention for Transformer-Based Detection Heads
Xiaohu Jiang, Ze Chen, Zhicheng Wang +2
After DETR was proposed, this novel transformer-based detection paradigm which performs several cross-attentions between object queries and feature maps for predictions has subsequ…
SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection
Ze Chen, Zhihang Fu, Rongxin Jiang +2
Based on the framework of multiple instance learning (MIL), tremendous works have promoted the advances of weakly supervised object detection (WSOD). However, most MIL-based method…