activity
20232026
most citedCategory Feature Transformer for Semantic Segmentation

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

MaST: Motion-aware Sparse Pipeline for Lightweight Object Tracking

Qingmao Wei, Fagui Liu, Dengke Zhang +2

Transformer-based object trackers are renowned for their strong performance, yet dense token processing often leads to prohibitive computational cost, limiting real-time deployment…

cs.CV2026

ModuSeg: Decoupling Object Discovery and Semantic Retrieval for Training-Free Weakly Supervised Segmentation

Qingze He, Fagui Liu, Dengke Zhang +2

Weakly supervised semantic segmentation aims to achieve pixel-level predictions using image-level labels. Existing methods typically entangle semantic recognition and object locali…

cs.CV2024

EK-Net:Real-time Scene Text Detection with Expand Kernel Distance

Boyuan Zhu, Fagui Liu, Xi Chen +1

Recently, scene text detection has received significant attention due to its wide application. However, accurate detection in complex scenes of multiple scales, orientations, and c…

cs.CV2023

Dynamic Token Pruning in Plain Vision Transformers for Semantic Segmentation

Quan Tang, Bowen Zhang, Jiajun Liu +2

Vision transformers have achieved leading performance on various visual tasks yet still suffer from high computational complexity. The situation deteriorates in dense prediction ta…

cs.CV20231 cited

Category Feature Transformer for Semantic Segmentation

Quan Tang, Chuanjian Liu, Fagui Liu +5

Aggregation of multi-stage features has been revealed to play a significant role in semantic segmentation. Unlike previous methods employing point-wise summation or concatenation f…