BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation

Low-level details and high-level semantics are both essential to the semantic segmentation task. However, to speed up the model inference, current approaches almost always sacrifice the low-level details, leading to a considerable decrease in accuracy. We propose to treat these spatial details and c...

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Veröffentlicht in:	International journal of computer vision Jg. 129; H. 11; S. 3051 - 3068
Hauptverfasser:	Yu, Changqian, Gao, Changxin, Wang, Jingbo, Yu, Gang, Shen, Chunhua, Sang, Nong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.11.2021 Springer Springer Nature B.V
Schlagworte:	Accuracy Agglomeration Artificial Intelligence Channel capacity Channels Computer Imaging Computer Science Image Processing and Computer Vision Inference Pattern Recognition Pattern Recognition and Graphics Real time Representations Semantic segmentation Semantics Vision Real-time processing Deep learning Bilateral network Semantic segmentation
ISSN:	0920-5691, 1573-1405
Online-Zugang:	Volltext
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