4 papers · 1 filter
0.5%>100%: Bidirectional Reciprocal Learning for Referring Image Segmentation
Xiaoqiang Lu, Licheng Jiao, Lingling Li +5
Recent advances in vision foundation models (VFMs) have shown remarkable capabilities across diverse unimodal visual tasks. However, adapting VFMs to referring image segmentation (…
DeCo: Efficient Decouple-to-Couple Learning for Multi-Task Visual Grounding
Xiaoqiang Lu, Licheng Jiao, Long Sun +5
Multi-task visual grounding requires models to jointly understand linguistic semantics and perform accurate visual localization and segmentation. Despite the success of multimodal…
Turbulence-Robust Dynamic Object Segmentation with Multi-Signal Priors and SAM2 Refinement
Bolian Peng, Ying Tang, Xu Liu +2
This technical report presents our solution for the CVPR 2026 UG2+ Challenge Track 3: Dynamic Object Segmentation in Turbulence (DOST). We design a training-free multi-signal segme…
Technique Report of CVPR 2024 PBDL Challenges
Ying Fu, Yu Li, Shaodi You +96
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…