10 citations · 40 across the 8 of their papers we have counts for
6 papers · 1 filter
Acquire and then Adapt: Squeezing out Text-to-Image Model for Image Restoration
Junyuan Deng, Xinyi Wu, Yongxing Yang +3
Recently, pre-trained text-to-image (T2I) models have been extensively adopted for real-world image restoration because of their powerful generative prior. However, controlling the…
Few-Shot 3D Point Cloud Semantic Segmentation via Stratified Class-Specific Attention Based Transformer Network
Canyu Zhang, Zhenyao Wu, Xinyi Wu +2
3D point cloud semantic segmentation aims to group all points into different semantic categories, which benefits important applications such as point cloud scene reconstruction and…
Parametric Surface Constrained Upsampler Network for Point Cloud
Pingping Cai, Zhenyao Wu, Xinyi Wu +1
Designing a point cloud upsampler, which aims to generate a clean and dense point cloud given a sparse point representation, is a fundamental and challenging problem in computer vi…
Cross-domain Few-shot Segmentation with Transductive Fine-tuning
Yuhang Lu, Xinyi Wu, Zhenyao Wu +1
Few-shot segmentation (FSS) expects models trained on base classes to work on novel classes with the help of a few support images. However, when there exists a domain gap between t…
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
Xinyi Wu, Zhenyao Wu, Hao Guo +2
Semantic segmentation of nighttime images plays an equally important role as that of daytime images in autonomous driving, but the former is much more challenging due to poor illum…
From Shadow Generation to Shadow Removal
Zhihao Liu, Hui Yin, Xinyi Wu +3
Shadow removal is a computer-vision task that aims to restore the image content in shadow regions. While almost all recent shadow-removal methods require shadow-free images for tra…