10 citations · 11 across the 3 of their papers we have counts for
4 papers
How to Exploit the Transferability of Learned Image Compression to Conventional Codecs
Jan P. Klopp, Keng-Chi Liu, Liang-Gee Chen +1
Lossy image compression is often limited by the simplicity of the chosen loss measure. Recent research suggests that generative adversarial networks have the ability to overcome th…
Joint Pruning & Quantization for Extremely Sparse Neural Networks
Po-Hsiang Yu, Sih-Sian Wu, Jan P. Klopp +2
We investigate pruning and quantization for deep neural networks. Our goal is to achieve extremely high sparsity for quantized networks to enable implementation on low cost and low…
Utilising Low Complexity CNNs to Lift Non-Local Redundancies in Video Coding
Jan P. Klopp, Liang-Gee Chen, Shao-Yi Chien
Digital media is ubiquitous and produced in ever-growing quantities. This necessitates a constant evolution of compression techniques, especially for video, in order to maintain ef…
What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing
Keng-Chi Liu, Yi-Ting Shen, Jan P. Klopp +1
Scene Parsing is a crucial step to enable autonomous systems to understand and interact with their surroundings. Supervised deep learning methods have made great progress in solvin…