Hugging Face Trending Papers
Jun 23

Training-free Cross-domain Few-shot Segmentation via Robust Semantic Representation and Matching

Cross-domain Few-shot Segmentation (CD-FSS) aims to transfer knowledge learned from source domain to distinct target domains, segmenting unseen target classes with only a few annotated samples. Although existing methods have made significant progress, they still rely on training or fine-tuning processes, which incur high computational costs and risk overfitting.

arXiv Computer Vision
3d ago

UINO-FSS: Unifying Representation Learning and Few-shot Segmentation via Hierarchical Distillation and Mamba-HyperCorrelation

The paper introduces UINO-FSS, a unified framework for few-shot semantic segmentation that merges knowledge from DINOv2 and SAM into a single-encoder architecture. It employs coarse-to-fine multimodal distillation, a bottleneck adapter for embedding alignment, a meta-visual prompt generator, and a mask decoder, enhanced by Mamba-based 4D correlation mining. Experiments on PASCAL-5i and COCO-20i demonstrate state‑of‑the‑art performance in 1‑shot settings, achieving 80.6% mIoU on PASCAL-5i and 64.5% on COCO-20i.

By Wei Zhuo, Zhiyue Tang, Wufeng Xue, Hao Ding, Junkai Ji, Linlin Shen