3 citations · 4 across the 6 of their papers we have counts for
6 papers
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…
Instruct2See: Learning to Remove Any Obstructions Across Distributions
Junhang Li, Yu Guo, Chuhua Xian +1
Images are often obstructed by various obstacles due to capture limitations, hindering the observation of objects of interest. Most existing methods address occlusions from specifi…
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…
OneRestore: A Universal Restoration Framework for Composite Degradation
Yu Guo, Yuan Gao, Yuxu Lu +3
In real-world scenarios, image impairments often manifest as composite degradations, presenting a complex interplay of elements such as low light, haze, rain, and snow. Despite thi…
Zero-shot Object Counting with Good Exemplars
Huilin Zhu, Jingling Yuan, Zhengwei Yang +4
Zero-shot object counting (ZOC) aims to enumerate objects in images using only the names of object classes during testing, without the need for manual annotations. However, a criti…