SCANet: Real-Time Face Parsing Using Spatial and Channel Attention-Reference-Cited by-同舟云学术

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SCANet: Real-Time Face Parsing Using Spatial and Channel Attention

Published:2023-06-25 Issue: Volume: Page:
ISSN:
Container-title:2023 20th International Conference on Ubiquitous Robots (UR)
language:
Short-container-title:

Author:

Han Seungeun¹,Yoon Hosub²

Affiliation:

1. University of Science and Technology,Department of Artificial Intelligence,Daejeon,Republic of Korea,34129

2. Electronics and Telecommuications Research Institute(ETRI),Human Robot Interaction Section, Mobility Robot Research Division, Superintelligence Creative Research Laboratory,Daejeon,Republic of Korea,34129

Funder

ETRI

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10202211/10202162/10202537.pdf?arnumber=10202537

Reference16 articles.

1. An end-to-end face parsing model using channel and spatial attentions

2. In-place Activated BatchNorm for Memory-Optimized Training of DNNs

3. Cbam: Convolutional block attention module;woo;Proceedings of the European Conference on Computer Vision (ECCV),0

4. SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning

5. Edge-Aware Graph Representation Learning and Reasoning for Face Parsing

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Occlusion-aware deep convolutional neural network via homogeneous Tanh-transforms for face parsing;Image and Vision Computing;2024-08

2. Advancing Face Parsing in Real-World: Synergizing Self-Attention and Self-Distillation;IEEE Access;2024

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