1 citations · 1 across the 5 of their papers we have counts for
6 papers
Coding Standards as Anchors for the CVPR CLIC video track
Théo Ladune, Pierrick Philippe
In 2021, a new track has been initiated in the Challenge for Learned Image Compression~: the video track. This category proposes to explore technologies for the compression of shor…
Conditional Coding for Flexible Learned Video Compression
Théo Ladune, Pierrick Philippe, Wassim Hamidouche +2
This paper introduces a novel framework for end-to-end learned video coding. Image compression is generalized through conditional coding to exploit information from reference frame…
Conditional Coding and Variable Bitrate for Practical Learned Video Coding
Théo Ladune, Pierrick Philippe, Wassim Hamidouche +2
This paper introduces a practical learned video codec. Conditional coding and quantization gain vectors are used to provide flexibility to a single encoder/decoder pair, which is a…
Optical Flow and Mode Selection for Learning-based Video Coding
Théo Ladune, Pierrick Philippe, Wassim Hamidouche +2
This paper introduces a new method for inter-frame coding based on two complementary autoencoders: MOFNet and CodecNet. MOFNet aims at computing and conveying the Optical Flow and…
ModeNet: Mode Selection Network For Learned Video Coding
Théo Ladune, Pierrick Philippe, Wassim Hamidouche +2
In this paper, a mode selection network (ModeNet) is proposed to enhance deep learning-based video compression. Inspired by traditional video coding, ModeNet purpose is to enable c…
Binary Probability Model for Learning Based Image Compression
Théo Ladune, Pierrick Philippe, Wassim Hamidouche +2
In this paper, we propose to enhance learned image compression systems with a richer probability model for the latent variables. Previous works model the latents with a Gaussian or…