1 citations · 1 across the 5 of their papers we have counts for
5 papers
DRRNet: Macro-Micro Feature Fusion and Dual Reverse Refinement for Camouflaged Object Detection
Jianlin Sun, Xiaolin Fang, Juwei Guan +3
The core challenge in Camouflage Object Detection (COD) lies in the indistinguishable similarity between targets and backgrounds in terms of color, texture, and shape. This causes…
Enhancing Self-Supervised Fine-Grained Video Object Tracking with Dynamic Memory Prediction
Zihan Zhou, Changrui Dai, Aibo Song +1
Successful video analysis relies on accurate recognition of pixels across frames, and frame reconstruction methods based on video correspondence learning are popular due to their e…
Knowledge Rectification for Camouflaged Object Detection: Unlocking Insights from Low-Quality Data
Juwei Guan, Xiaolin Fang, Donghyun Kim +4
Low-quality data often suffer from insufficient image details, introducing an extra implicit aspect of camouflage that complicates camouflaged object detection (COD). Existing COD…
Keypoint Abstraction using Large Models for Object-Relative Imitation Learning
Xiaolin Fang, Bo-Ruei Huang, Jiayuan Mao +4
Generalization to novel object configurations and instances across diverse tasks and environments is a critical challenge in robotics. Keypoint-based representations have been prov…
Embodied Uncertainty-Aware Object Segmentation
Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez
We introduce uncertainty-aware object instance segmentation (UncOS) and demonstrate its usefulness for embodied interactive segmentation. To deal with uncertainty in robot percepti…