Lightweight multi-scale convolutional neural network for real time stereo matching
Authors:
- Yanbing XueYXYanbing Xue
- Doudou ZhangDZDoudou Zhang
- Leida LiLLLeida Li
- Shiyin LiSLShiyin Li
- Yuxin WangYWYuxin Wang
- 15 June 2022
- journal article
- research article
- Published by Elsevier in Image and Vision Computing
- Vol. 124
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61872270)
This publication has 8 references indexed in Scilit:
- CLN: Cross-Domain Learning Network for 2D Image-Based 3D Shape RetrievalIEEE Transactions on Circuits and Systems for Video Technology, 2021
- A Survey on Deep Learning Techniques for Stereo-Based Depth EstimationIEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
- M-GCN: Multi-Branch Graph Convolution Network for 2D Image-based on 3D Model RetrievalIEEE Transactions on Multimedia, 2020
- Deep bilateral learning for real-time image enhancementACM Transactions on Graphics, 2017
- Deconvolution and Checkerboard Artifacts2016
- Spatial Pyramid Pooling in Deep Convolutional Networks for Visual RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
- Adaptive support-weight approach for correspondence searchIEEE Transactions on Pattern Analysis and Machine Intelligence, 2006
- A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence AlgorithmsInternational Journal of Computer Vision, 2002