38 citations · 40 across the 6 of their papers we have counts for
6 papers
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…
MorphText: Deep Morphology Regularized Arbitrary-shape Scene Text Detection
Chengpei Xu, Wenjing Jia, Ruomei Wang +2
Bottom-up text detection methods play an important role in arbitrary-shape scene text detection but there are two restrictions preventing them from achieving their great potential,…
Seeing Text in the Dark: Algorithm and Benchmark
Chengpei Xu, Hao Fu, Long Ma +6
Localizing text in low-light environments is challenging due to visual degradations. Although a straightforward solution involves a two-stage pipeline with low-light image enhancem…
MFPNet: Multi-scale Feature Propagation Network For Lightweight Semantic Segmentation
Guoan Xu, Wenjing Jia, Tao Wu +1
In contrast to the abundant research focusing on large-scale models, the progress in lightweight semantic segmentation appears to be advancing at a comparatively slower pace. Howev…
CARD: Semantic Segmentation with Efficient Class-Aware Regularized Decoder
Ye Huang, Di Kang, Liang Chen +5
Semantic segmentation has recently achieved notable advances by exploiting "class-level" contextual information during learning. However, these approaches simply concatenate class-…