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eess.IV2022
Slimmable Video Codec
Zhaocheng Liu, Luis Herranz, Fei Yang +4
Neural video compression has emerged as a novel paradigm combining trainable multilayer neural networks and machine learning, achieving competitive rate-distortion (RD) performance…
eess.IV2022
DCNGAN: A Deformable Convolutional-Based GAN with QP Adaptation for Perceptual Quality Enhancement of Compressed Video
Saiping Zhang, Luis Herranz, Marta Mrak +3
In this paper, we propose a deformable convolution-based generative adversarial network (DCNGAN) for perceptual quality enhancement of compressed videos. DCNGAN is also adaptive to…
eess.IV2021
DVC-P: Deep Video Compression with Perceptual Optimizations
Saiping Zhang, Marta Mrak, Luis Herranz +3
Recent years have witnessed the significant development of learning-based video compression methods, which aim at optimizing objective or perceptual quality and bit rates. In this…