EMSFomer: Efficient Multi-Scale Transformer for Real-Time Semantic Segmentation

Transformer-based models have achieved impressive performance in semantic segmentation in recent years. However, the multi-head self-attention mechanism in Transformers incurs significant computational overhead and becomes impractical for real-time applications due to its high complexity and large l...

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Bibliographic Details
Main Authors: Zhengyu Xia, Joohee Kim
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10852306/
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