4 papers
CMaP-SAM: Contraction Mapping Prior for SAM-driven Few-shot Segmentation
Shuai Chen, Fanman Meng, Liming Lei +5
Few-shot segmentation (FSS) aims to segment new classes using few annotated images. While recent FSS methods have shown considerable improvements by leveraging Segment Anything Mod…
DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation
Shuai Chen, Fanman Meng, Xiwei Zhang +4
This paper presents DFR (Decompose, Fuse and Reconstruct), a novel framework that addresses the fundamental challenge of effectively utilizing multi-modal guidance in few-shot segm…
Your Demands Deserve More Bits: Referring Semantic Image Compression at Ultra-low Bitrate
Chenhao Wu, Qingbo Wu, Haoran Wei +5
With the help of powerful generative models, Semantic Image Compression (SIC) has achieved impressive performance at ultra-low bitrate. However, due to coarse-grained visual-semant…
No Re-Train, More Gain: Upgrading Backbones with Diffusion model for Pixel-Wise and Weakly-Supervised Few-Shot Segmentation
Shuai Chen, Fanman Meng, Chenhao Wu +5
Few-Shot Segmentation (FSS) aims to segment novel classes using only a few annotated images. Despite considerable progress under pixel-wise support annotation, current FSS methods…