1.4k citations · 2.6k across the 155 of their papers we have counts for
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Advancing Learned Video Compression with In-loop Frame Prediction
Ren Yang, Radu Timofte, Luc Van Gool
Recent years have witnessed an increasing interest in end-to-end learned video compression. Most previous works explore temporal redundancy by detecting and compressing a motion ma…
Implicit Neural Representations for Image Compression
Yannick Strümpler, Janis Postels, Ren Yang +2
Recently Implicit Neural Representations (INRs) gained attention as a novel and effective representation for various data types. Thus far, prior work mostly focused on optimizing t…
Perceptual Learned Video Compression with Recurrent Conditional GAN
Ren Yang, Radu Timofte, Luc Van Gool
This paper proposes a Perceptual Learned Video Compression (PLVC) approach with recurrent conditional GAN. We employ the recurrent auto-encoder-based compression network as the gen…
Fourier Space Losses for Efficient Perceptual Image Super-Resolution
Dario Fuoli, Luc Van Gool, Radu Timofte
Many super-resolution (SR) models are optimized for high performance only and therefore lack efficiency due to large model complexity. As large models are often not practical in re…
An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement
Dario Fuoli, Zhiwu Huang, Danda Pani Paudel +2
Video enhancement is a challenging problem, more than that of stills, mainly due to high computational cost, larger data volumes and the difficulty of achieving consistency in the…
Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model
Ren Yang, Fabian Mentzer, Luc Van Gool +1
The past few years have witnessed increasing interests in applying deep learning to video compression. However, the existing approaches compress a video frame with only a few numbe…
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
Ren Yang, Fabian Mentzer, Luc Van Gool +1
In this paper, we propose a Hierarchical Learned Video Compression (HLVC) method with three hierarchical quality layers and a recurrent enhancement network. The frames in the first…
Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement
Zhiwu Huang, Danda Pani Paudel, Guanju Li +3
This paper introduces a divide-and-conquer inspired adversarial learning (DACAL) approach for photo enhancement. The key idea is to decompose the photo enhancement process into hie…