12 citations · 12 across the 6 of their papers we have counts for
7 papers
N-O Cool-chic: reconcile fast encoding with lightweight decoding for neural image compression
Théophile Blard, Théo Ladune, Pierrick Philippe +2
Overfitted image codecs achieve strong compression performance and low decoder complexity by learning a lightweight decoder for each image. Such codecs include Cool-chic, which pre…
Spatial Competition for Low-Complexity Learned Image Compression
Théophile Blard, Pierrick Philippe, Théo Ladune +2
Autoencoder-based image codecs achieve state-of-the-art compression performance but often incur high computational complexity, particularly at decoding time. This work introduces a…
Cool-chic 5.0: Faster Encoding and Inter-Feature Entropy Modeling for Overfitted Image Compression
Théo Ladune, Pierrick Philippe, Pierre Jaffuer +4
Overfitted codecs compress an image by learning a decoder tailored to the content during the encoding. As such, they trade increased encoding complexity for strong compression perf…
Efficient Sub-pixel Motion Compensation in Learned Video Codecs
Théo Ladune, Thomas Leguay, Pierrick Philippe +2
Motion compensation is a key component of video codecs. Conventional codecs (HEVC and VVC) have carefully refined this coding step, with an important focus on sub-pixel motion comp…
Upsampling Improvement for Overfitted Neural Coding
Pierrick Philippe, Théo Ladune, Gordon Clare +3
Neural image compression, based on auto-encoders and overfitted representations, relies on a latent representation of the coded signal. This representation needs to be compact and…
Cool-chic video: Learned video coding with 800 parameters
Thomas Leguay, Théo Ladune, Pierrick Philippe +1
We propose a lightweight learned video codec with 900 multiplications per decoded pixel and 800 parameters overall. To the best of our knowledge, this is one of the neural video co…
Cool-Chic: Perceptually Tuned Low Complexity Overfitted Image Coder
Théo Ladune, Pierrick Philippe, Gordon Clare +2
This paper summarises the design of the Cool-Chic candidate for the Challenge on Learned Image Compression. This candidate attempts to demonstrate that neural coding methods can le…