Self-supervised depth super-resolution with contrastive multiview pre-training

Xin Qiao; Chenyang Ge; Chaoqiang Zhao; Fabio Tosi; Matteo Poggi; Stefano Mattoccia

doi:10.1016/j.neunet.2023.09.023

ScienceGate Book Chapters

JOURNAL ARTICLE

Self-supervised depth super-resolution with contrastive multiview pre-training

Xin Qiao Chenyang Ge Chaoqiang Zhao Fabio Tosi Matteo Poggi Stefano Mattoccia

Year: 2023 Journal: Neural Networks Vol: 168 Pages: 223-236 Publisher: Elsevier BV

DOI: 10.1016/j.neunet.2023.09.023

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Artificial intelligence Pattern recognition (psychology) Segmentation Redundancy (engineering) Generalization Mutual information Machine learning Computer vision Mathematics

Metrics

Cited By

1.64

FWCI (Field Weighted Citation Impact)

Refs

0.81

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

Optical measurement and interference techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Self-supervised depth super-resolution with contrastive multiview pre-training

Metrics

Citation History

Topics

Related Documents

Multilevel Contrastive Multiview Clustering With Dual Self-Supervised Learning

Optimizing Medical Diagnostic Models with Self-Supervised Contrastive Pre-Training

Depth based super-resolution for multiview images

Dense Contrastive Learning for Self-Supervised Visual Pre-Training

Contrastive Self-Supervised Pre-Training for Video Quality Assessment