235 citations · 244 across the 6 of their papers we have counts for
6 papers
Wrapper-Aware Rate-Distortion Optimization in Feature Coding for Machines
Samuel Fernández-Menduiña, Hyomin Choi, Fabien Racapé +2
Feature coding for machines (FCM) is a lossy compression paradigm for split-inference. The transmitter encodes the outputs of the first part of a neural network before sending them…
DeDelayed: Deleting Remote Inference Delay via On-Device Correction
Dan Jacobellis, Mateen Ulhaq, Fabien Racapé +2
Video comprises the vast majority of bits that are generated daily, and is the primary signal driving current innovations in robotics, remote sensing, and wearable technology. Yet,…
CompressAI-Vision: Open-source software to evaluate compression methods for computer vision tasks
Hyomin Choi, Heeji Han, Chris Rosewarne +1
With the increasing use of neural network (NN)-based computer vision applications that process image and video data as input, interest has emerged in video compression technology o…
Entropy Coding Improvement for Low-complexity Compressive Auto-encoders
Franck Galpin, Muhammet Balcilar, Frédéric Lefebvre +2
End-to-end image and video compression using auto-encoders (AE) offers new appealing perspectives in terms of rate-distortion gains and applications. While most complex models are…
End-to-end optimized image compression for multiple machine tasks
Lahiru D. Chamain, Fabien Racapé, Jean Bégaint +2
An increasing share of captured images and videos are transmitted for storage and remote analysis by computer vision algorithms, rather than to be viewed by humans. Contrary to tra…
CompressAI: a PyTorch library and evaluation platform for end-to-end compression research
Jean Bégaint, Fabien Racapé, Simon Feltman +1
This paper presents CompressAI, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs…