BVI-DVC Part 1

Deep learning methods are increasingly being applied in the optimisation of video compression algorithms and can achieve significantly enhanced coding gains, compared to conventional approaches. Such approaches often employ Convolutional Neural Networks (CNNs) which are trained on databases with relatively limited content coverage. BVI-DVC is a new extensive and representative video database for training CNN-based coding tools, which contains 772 sequences at various spatial resolutions from 270p to 2160p. Experimental results show that the database produces significant improvements in terms of coding gains over three existing (commonly used) image/video training databases.

Complete download (zip, 83.8 GiB)

Alternative title A Training Database for Deep Video Compression
Creator(s) Fan Zhang, Di Ma, David Bull
Publication date 30 Nov 2021
Language eng
Publisher University of Bristol
Licence Non-Commercial Government Licence for public sector information
DOI 10.5523/bris.3h0hduxrq4awq2ffvhabjzbzi1
Citation Fan Zhang, Di Ma, David Bull (2021): BVI-DVC Part 1.
Total size 83.8 GiB


Data Resources