Search Results for author: Quan Tang

Found 7 papers, 4 papers with code

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

no code implementations22 Jan 2024 Boyuan Zhu, Fagui Liu, Xi Chen, Quan Tang

Recently, scene text detection has received significant attention due to its wide application.

Scene Text Detection Text Detection

Boosting Semantic Segmentation from the Perspective of Explicit Class Embeddings

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.

Segmentation Semantic Segmentation

Category Feature Transformer for Semantic Segmentation

1 code implementation10 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.

Segmentation Semantic Segmentation

Dynamic Token Pruning in Plain Vision Transformers for 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.

Image Classification Segmentation +1

EPRNet: Efficient Pyramid Representation Network for Real-Time Street Scene Segmentation

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.

Image Classification Scene Segmentation +1

Attention-guided Chained Context Aggregation for Semantic Segmentation

3 code implementations27 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.

Semantic Segmentation

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