End-To-End Depth Map Compression Framework Via Rgb-To-Depth Structure Priors Learning-Reference-Cited by-同舟云学术

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End-To-End Depth Map Compression Framework Via Rgb-To-Depth Structure Priors Learning

Published:2022-10-16 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Image Processing (ICIP)
language:
Short-container-title:

Author:

Chen Minghui¹,Zhang Pingping²,Chen Zhuo³,Zhang Yun⁴,Wang Xu¹,Kwong Sam²

Affiliation:

1. Shenzhen University,College of Computer Science and Software Engineering,China

2. City University of Hong Kong,Department of Computer Science,China

3. A*STAR,Institute for Infocomm Research,Singapore

4. Chinese Academy of Sciences,Shenzhen Institutes of Advanced Technology,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9897158/9897159/09898073.pdf?arnumber=9898073

Reference28 articles.

1. Adapting standard video codecs for depth streaming;pece;In JVRC11 Joint Virtual Reality Conference of EGVE - EuroVR,2011

2. Enhanced Invertible Encoding for Learned Image Compression

3. A low complexity depth map compression approach for Microsoft Kinect devices

4. Kinect-Like Depth Data Compression

5. End-to-end optimized image compression with attention mechanism;zhou;IEEE Conference on Computer Vision and Pattern Recognition Workshops,2019

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. Saliency-Guided Point Cloud Compression for 3D Live Reconstruction;Multimodal Technologies and Interaction;2024-05-03

2. End-to-End Variable-Rate Learning-Based Depth Compression Guided by Deep Correlation Features;Journal of Signal Processing Systems;2024-01

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