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29th Meeting: by teleconference, DE, January 2023 2023-01-06 13:35
EE1-2.4: CNN filter Based on RPR-based SR Combined with GOP Level Adaptive Resolution
Abstract
This contribution reports the EE1-2.4 test results, which is a combination of JVET-AB0093 and JVET-Z0065 test 2.1.1. At each GOP level, the encoder can adaptively select a scale factor from 1.0x and 2.0x and CNN-based super-resolution is utilized for is the latter case. Compared with VTM-11.0-nnvc-2.0, the test 2.4.1 experimental results show {-4.14%(Y), -0.33%(U), -0.22%(V)} and {-3.73%(Y), -3.07%(U), -1.15%(V)} and the test 2.4.2 experimental results show {-4.98%(Y), 0.07%(U), -0.78%(V)} and {-3.73%(Y), -3.07%(U), -1.15%(V)} BD-rate gains on average (A1 and A2 classes), under AI and RA configurations.
JVET-AC0052 EE1-2.4: CNN filter Based on RPR-based SR Combined with GOP Level Adaptive Resolution [S. Huang, C. Jung (Xidian Univ.), Y. Liu, M. Li (OPPO), J. Nam, S. Yoo, J. Lim, S. H. Kim (LGE)]

This contribution reports the EE1-2.4 test results, which is a combination of JVET-AB0093 and JVET-Z0065 test 2.1.1. At each GOP level, the encoder can adaptively select a scale factor from 1.0x and 2.0x and CNN-based super-resolution is utilized for is the latter case. Compared with VTM-11.0-nnvc-2.0, the test 2.4.1 experimental results show {-4.14%(Y), -0.33%(U), -0.22%(V)} and {-3.73%(Y), -3.07%(U), -1.15%(V)} and the test 2.4.2 experimental results show {-4.98%(Y), 0.07%(U), -0.78%(V)} and {-3.73%(Y), -3.07%(U), -1.15%(V)} BD-rate gains on average (A1 and A2 classes), under AI and RA configurations.

As a general comment, the constraint of 10% rate matching and showing PSNR graphs allows much better interpretation of SR results.

It was also commented that it would be beneficial to provide SSIM resuls in SR proposals.

Decisions
It was also commented that it would be beneficial to provide SSIM resuls in SR proposals.
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