Few-shot segmentation via divide-and-conquer proxies
Few-Shot segmentation (FSS) is a marginally explored but challenging task that aims to
identify unseen classes of objects with only a handful of densely annotated samples. By and …
identify unseen classes of objects with only a handful of densely annotated samples. By and …
Few-shot semantic segmentation: a review on recent approaches
Z Chang, Y Lu, X Ran, X Gao, X Wang - Neural Computing and …, 2023 - Springer
Few-shot semantic segmentation (FSS) is a challenging task that aims to learn to segment
novel categories with only a few labeled images, and it has a wide range of real-world …
novel categories with only a few labeled images, and it has a wide range of real-world …
Pixel matching network for cross-domain few-shot segmentation
H Chen, Y Dong, Z Lu, Y Yu… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
Abstract Few-Shot Segmentation (FSS) aims to segment the novel class images with a few
annotated samples. In the past, numerous studies have concentrated on cross-category …
annotated samples. In the past, numerous studies have concentrated on cross-category …
MMT: cross domain few-shot learning via meta-memory transfer
Few-shot learning aims to recognize novel categories solely relying on a few labeled
samples, with existing few-shot methods primarily focusing on the categories sampled from …
samples, with existing few-shot methods primarily focusing on the categories sampled from …
MetaScleraSeg: an effective meta-learning framework for generalized sclera segmentation
Sclera segmentation is a key component of sclera recognition, which decides the region-of-
interest (ROI) for recognition and has a considerable impact on the overall performance. In …
interest (ROI) for recognition and has a considerable impact on the overall performance. In …
Dense affinity matching for few-shot segmentation
Abstract Few-Shot Segmentation (FSS) aims to segment the novel class images with a few
annotated samples. In this paper, we propose a dense affinity matching (DAM) framework to …
annotated samples. In this paper, we propose a dense affinity matching (DAM) framework to …
Visual and textual prior guided mask assemble for few-shot segmentation and beyond
Few-shot segmentation (FSS) aims to segment the novel classes with a few annotated
images. Due to CLIP's advantages of aligning visual and textual information, the integration …
images. Due to CLIP's advantages of aligning visual and textual information, the integration …
APSeg: Auto-Prompt Network for Cross-Domain Few-Shot Semantic Segmentation
Few-shot semantic segmentation (FSS) endeavors to segment unseen classes with only a
few labeled samples. Current FSS methods are commonly built on the assumption that their …
few labeled samples. Current FSS methods are commonly built on the assumption that their …
Cross-Domain Few-Shot Segmentation via Iterative Support-Query Correspondence Mining
Abstract Cross-Domain Few-Shot Segmentation (CD-FSS) poses the challenge of
segmenting novel categories from a distinct domain using only limited exemplars. In this …
segmenting novel categories from a distinct domain using only limited exemplars. In this …
Domain-Rectifying Adapter for Cross-Domain Few-Shot Segmentation
Few-shot semantic segmentation (FSS) has achieved great success on segmenting objects
of novel classes supported by only a few annotated samples. However existing FSS …
of novel classes supported by only a few annotated samples. However existing FSS …