38 citations · 55 across the 14 of their papers we have counts for
5 papers · 1 filter
SCASeg: Strip Cross-Attention for Efficient Semantic Segmentation
Guoan Xu, Jiaming Chen, Wenfeng Huang +3
The Vision Transformer (ViT) has achieved notable success in computer vision, with its variants widely validated across various downstream tasks, including semantic segmentation. H…
Efficient Semantic Segmentation via Lightweight Multiple-Information Interaction Network
Yangyang Qiu, Guoan Xu, Guangwei Gao +3
Recently, integrating the local modeling capabilities of Convolutional Neural Networks (CNNs) with the global dependency strengths of Transformers has created a sensation in the se…
ReviveDiff: A Universal Diffusion Model for Restoring Images in Adverse Weather Conditions
Wenfeng Huang, Guoan Xu, Wenjing Jia +2
Images captured in challenging environments--such as nighttime, smoke, rainy weather, and underwater--often suffer from significant degradation, resulting in a substantial loss of…
MacFormer: Semantic Segmentation with Fine Object Boundaries
Guoan Xu, Wenfeng Huang, Tao Wu +5
Semantic segmentation involves assigning a specific category to each pixel in an image. While Vision Transformer-based models have made significant progress, current semantic segme…
HAFormer: Unleashing the Power of Hierarchy-Aware Features for Lightweight Semantic Segmentation
Guoan Xu, Wenjing Jia, Tao Wu +2
Both Convolutional Neural Networks (CNNs) and Transformers have shown great success in semantic segmentation tasks. Efforts have been made to integrate CNNs with Transformer models…