most citedFocus on Query: Adversarial Mining Transformer for Few-Shot Segmentation

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Towards Unsupervised Domain Bridging via Image Degradation in Semantic Segmentation

Wangkai Li, Rui Sun, Huayu Mai +1

Semantic segmentation suffers from significant performance degradation when the trained network is applied to a different domain. To address this issue, unsupervised domain adaptat…

cs.CV2024

Exploring Reliable Matching with Phase Enhancement for Night-time Semantic Segmentation

Yuwen Pan, Rui Sun, Naisong Luo +2

Semantic segmentation of night-time images holds significant importance in computer vision, particularly for applications like night environment perception in autonomous driving sy…

cs.CV2024

Localization and Expansion: A Decoupled Framework for Point Cloud Few-shot Semantic Segmentation

Zhaoyang Li, Yuan Wang, Wangkai Li +2

Point cloud few-shot semantic segmentation (PC-FSS) aims to segment targets of novel categories in a given query point cloud with only a few annotated support samples. The current…

cs.CV2024

Image-to-Image Matching via Foundation Models: A New Perspective for Open-Vocabulary Semantic Segmentation

Yuan Wang, Rui Sun, Naisong Luo +2

Open-vocabulary semantic segmentation (OVS) aims to segment images of arbitrary categories specified by class labels or captions. However, most previous best-performing methods, wh…

cs.CV2023★ 4 cited

Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation

Yuan Wang, Naisong Luo, Tianzhu Zhang

Few-shot segmentation (FSS) aims to segment objects of new categories given only a handful of annotated samples. Previous works focus their efforts on exploring the support informa…