no code implementations • 22 Jan 2024 • Boyuan Zhu, Fagui Liu, Xi Chen, Quan Tang
Recently, scene text detection has received significant attention due to its wide application.
no code implementations • ICCV 2023 • Yuhe Liu, Chuanjian Liu, Kai Han, Quan Tang, Zengchang Qin
Following this observation, we propose ECENet, a new segmentation paradigm, in which class embeddings are obtained and enhanced explicitly during interacting with multi-stage image features.
1 code implementation • 10 Aug 2023 • Quan Tang, Chuanjian Liu, Fagui Liu, Yifan Liu, Jun Jiang, BoWen Zhang, Kai Han, Yunhe Wang
Aggregation of multi-stage features has been revealed to play a significant role in semantic segmentation.
1 code implementation • ICCV 2023 • Quan Tang, BoWen Zhang, Jiajun Liu, Fagui Liu, Yifan Liu
Experiments suggest that the proposed DToP architecture reduces on average $20\% - 35\%$ of computational cost for current semantic segmentation methods based on plain vision transformers without accuracy degradation.
1 code implementation • 12 Oct 2022 • BoWen Zhang, Zhi Tian, Quan Tang, Xiangxiang Chu, Xiaolin Wei, Chunhua Shen, Yifan Liu
We explore the capability of plain Vision Transformers (ViTs) for semantic segmentation and propose the SegVit.
Ranked #4 on Semantic Segmentation on COCO-Stuff test
no code implementations • IEEE Transactions on Intelligent Transportation Systems 2021 • Quan Tang, Fagui Liu, Jun Jiang, Yu Zhang
Current scene segmentation methods suffer from cumbersome model structures and high computational complexity, impeding their applications to real-world scenarios that require real-time processing.
3 code implementations • 27 Feb 2020 • Quan Tang, Fagui Liu, Tong Zhang, Jun Jiang, Yu Zhang
The way features propagate in Fully Convolutional Networks is of momentous importance to capture multi-scale contexts for obtaining precise segmentation masks.
Ranked #23 on Semantic Segmentation on SUN-RGBD