Compression Artifacts Reduction for Depth Map by Deep Intensity Guidance

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

1 Scopus Citations
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Author(s)

  • Xu Wang
  • Yun Zhang
  • Lin Ma
  • Jianmin Jiang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing – PCM 2017
Subtitle of host publication18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
EditorsBing Zeng, Qingming Huang, Abdulmotaleb El Saddik, Hongliang Li, Shuqiang Jiang, Xiaopeng Fan
PublisherSpringer, Cham
Pages863-872
Volume1
ISBN (electronic)9783319773803
ISBN (print)9783319773797
Publication statusPublished - 2018

Publication series

NameLecture Notes in Computer Science (including subseries Information Systems and Applications, incl. Internet/Web, and HCI)
PublisherSpringer, Cham
Volume10735
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Conference

Title18th Pacific-Rim Conference on Multimedia, PCM 2017
PlaceChina
CityHarbin
Period28 - 29 September 2017

Abstract

In this paper, we propose a intensity guided CNN (IG-Net) model, which learns an end-to-end mapping between the intensity image and distorted depth map to the uncompressed depth map. To eliminate the undesired blocking artifacts such as discontinuities around object boundary, two branches are designed to extract the high-frequency information from intensity image and depth map, respectively. Multi-scale feature fusion and enhancement layers are introduced in the main branch to strength the edge information of the restored depth map. Performance evaluation on JPEG compression artifacts shows the effectiveness and superiority of our proposed model compared with state-of-the-art methods.

Research Area(s)

  • Compression artifacts, Convolutional neural network, JPEG compression

Citation Format(s)

Compression Artifacts Reduction for Depth Map by Deep Intensity Guidance. / Zhang, Pingping; Wang, Xu; Zhang, Yun et al.
Advances in Multimedia Information Processing – PCM 2017: 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers. ed. / Bing Zeng; Qingming Huang; Abdulmotaleb El Saddik; Hongliang Li; Shuqiang Jiang; Xiaopeng Fan. Vol. 1 Springer, Cham, 2018. p. 863-872 (Lecture Notes in Computer Science (including subseries Information Systems and Applications, incl. Internet/Web, and HCI); Vol. 10735 ).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review