Adaptive coding unit size convolutional neural network for fast 3D-HEVC depth map intracoding

2021 ◽  
Vol 30 (04) ◽  
Author(s):  
Hua Zhang ◽  
Wangze Yao ◽  
Hongfei Huang ◽  
Yifan Wu ◽  
Guojun Dai
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Depth Map ◽  
Unit Size ◽  
Adaptive Coding ◽  
Coding Unit

scholarly journals A Normalized Convolutional Neural Network for Guided Sparse Depth Upsampling

2018 ◽  
Author(s):  
Jiashen Hua ◽  
Xiaojin Gong
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Color Image ◽  
State Of The Art ◽  
Depth Map ◽  
Sparse Data ◽  
Optimal Choice ◽  
Deep Convolutional Neural Networks ◽  
Normalized Convolution ◽  
Indoor And Outdoor

Guided sparse depth upsampling aims to upsample an irregularly sampled sparse depth map when an aligned high-resolution color image is given as guidance. When deep convolutional neural networks (CNNs) become the optimal choice to many applications nowadays, how to deal with irregular and sparse data still remains a non-trivial problem. Inspired by the classical normalized convolution operation, this work proposes a normalized convolutional layer (NCL) implemented in CNNs. Sparse data are therefore explicitly considered in CNNs by the separation of both data and filters into a signal part and a certainty part. Based upon NCLs, we design a normalized convolutional neural network (NCNN) to perform guided sparse depth upsampling. Experiments on both indoor and outdoor datasets show that the proposed NCNN models achieve state-of-the-art upsampling performance. Moreover, the models using NCLs gain a great generalization ability to different sparsity levels.

scholarly journals Color-Guided Depth Map Super Resolution Using Convolutional Neural Network

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 26666-26672 ◽  
Author(s):  
Min Ni ◽  
Jianjun Lei ◽  
Runmin Cong ◽  
Kaifu Zheng ◽  
Bo Peng ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Super Resolution ◽  
Depth Map

Depth Map Super-Resolution Based on Two-Channel Convolutional Neural Network

2018 ◽  
Vol 38 (10) ◽  
pp. 1010002
Author(s):  
李素梅 Li Sumei ◽  
雷国庆 Lei Guoqing ◽  
范如 Fan Ru
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Super Resolution ◽  
Depth Map

CONVOLUTIONAL NEURAL NETWORK BASED ALGORITHM FOR CECUM ACHIEVEMENT CONFIRMATION

2020 ◽  
Author(s):  
S Kashin ◽  
D Zavyalov ◽  
A Rusakov ◽  
V Khryashchev ◽  
A Lebedev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network
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