4 papers
CouCE: A Unified Causal Framework for Debiased Deep Metric Learning
Xin Yuan, Zhenyang Niu, Meiqi Wan +3
Deep Metric Learning (DML) often struggles with zero-shot generalization because standard objectives inherently capture what co-occurs rather than what causes similarity. Consequen…
Neptune-X: Active X-to-Maritime Generation for Universal Maritime Object Detection
Yu Guo, Shengfeng He, Yuxu Lu +5
Maritime object detection is essential for navigation safety, surveillance, and autonomous operations, yet constrained by two key challenges: the scarcity of annotated maritime dat…
Expanding Zero-Shot Object Counting with Rich Prompts
Huilin Zhu, Senyao Li, Jingling Yuan +5
Expanding pre-trained zero-shot counting models to handle unseen categories requires more than simply adding new prompts, as this approach does not achieve the necessary alignment…
FocalCount: Towards Class-Count Imbalance in Class-Agnostic Counting
Huilin Zhu, Jingling Yuan, Zhengwei Yang +3
In class-agnostic object counting, the goal is to estimate the total number of object instances in an image without distinguishing between specific categories. Existing methods oft…