20 citations · 57 across the 10 of their papers we have counts for
21 papers
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…
Multi-encoder Network for Parameter Reduction of a Kernel-based Interpolation Architecture
Issa Khalifeh, Marc Gorriz Blanch, Ebroul Izquierdo +1
Video frame interpolation involves the synthesis of new frames from existing ones. Convolutional neural networks (CNNs) have been at the forefront of the recent advances in this fi…
Complexity Reduction of Learned In-Loop Filtering in Video Coding
Woody Bayliss, Luka Murn, Ebroul Izquierdo +2
In video coding, in-loop filters are applied on reconstructed video frames to enhance their perceptual quality, before storing the frames for output. Conventional in-loop filters a…
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…
Assisting News Media Editors with Cohesive Visual Storylines
Gonçalo Marcelino, David Semedo, André Mourão +3
Creating a cohesive, high-quality, relevant, media story is a challenge that news media editors face on a daily basis. This challenge is aggravated by the flood of highly relevant…
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…