Laformer: Vision Transformer for Panoramic Image Semantic Segmentation-Reference-Cited by-同舟云学术

Laformer: Vision Transformer for Panoramic Image Semantic Segmentation

Published:2023 Issue: Volume:30 Page:1792-1796
ISSN:1070-9908
Container-title:IEEE Signal Processing Letters
language:
Short-container-title:IEEE Signal Process. Lett.

Author:

Yuan Zheng¹^ORCID,Wang Junhua²^ORCID,Lv Yuxin³^ORCID,Wang Ding³^ORCID,Fang Yi³^ORCID

Affiliation:

1. Academy for Engineering and Technology, Fudan University, Shanghai, China

2. Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronic, Fudan University, Shanghai, China

3. School of Information Science and Technology, Fudan University, Shanghai, China

Funder

National Key Research and Development Program of China

Natural Science Foundation of Jiangxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/97/10036333/10334022.pdf?arnumber=10334022

Reference36 articles.

1. DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation

2. DACS: Domain Adaptation via Cross-domain Mixed Sampling

3. Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

4. Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation

5. Capturing Omni-Range Context for Omnidirectional Segmentation

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