16 citations · 32 across the 8 of their papers we have counts for
8 papers
Stronger, Fewer, & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation
Zhixiang Wei, Lin Chen, Yi Jin +6
In this paper, we first assess and harness various Vision Foundation Models (VFMs) in the context of Domain Generalized Semantic Segmentation (DGSS). Driven by the motivation that…
Disentangle then Parse:Night-time Semantic Segmentation with Illumination Disentanglement
Zhixiang Wei, Lin Chen, Tao Tu +3
Most prior semantic segmentation methods have been developed for day-time scenes, while typically underperforming in night-time scenes due to insufficient and complicated lighting…
FreeDrag: Feature Dragging for Reliable Point-based Image Editing
Pengyang Ling, Lin Chen, Pan Zhang +3
To serve the intricate and varied demands of image editing, precise and flexible manipulation in image content is indispensable. Recently, Drag-based editing methods have gained im…
Model Doctor for Diagnosing and Treating Segmentation Error
Zhijie Jia, Lin Chen, Kaiwen Hu +3
Despite the remarkable progress in semantic segmentation tasks with the advancement of deep neural networks, existing U-shaped hierarchical typical segmentation networks still suff…
Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation
Lin Chen, Zhixiang Wei, Xin Jin +4
In unsupervised domain adaptation (UDA), directly adapting from the source to the target domain usually suffers significant discrepancies and leads to insufficient alignment. Thus,…
Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation
Lin Chen, Huaian Chen, Zhixiang Wei +4
Adversarial learning has achieved remarkable performances for unsupervised domain adaptation (UDA). Existing adversarial UDA methods typically adopt an additional discriminator to…