no code implementations • 9 Jul 2023 • Goluck Konuko, Stéphane Lathuilière, Giuseppe Valenzise
We address the problem of efficiently compressing video for conferencing-type applications.
no code implementations • 15 Mar 2023 • Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise, Frederic Dufaux
With the increased interest in immersive experiences, point cloud came to birth and was widely adopted as the first choice to represent 3D media.
no code implementations • 4 Nov 2022 • Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise, Frederic Dufaux
Following the advent of immersive technologies and the increasing interest in representing interactive geometrical format, 3D Point Clouds (PC) have emerged as a promising solution and effective means to display 3D visual information.
1 code implementation • 1 Jul 2021 • Dat Thanh Nguyen, Maurice Quach, Giuseppe Valenzise, Pierre Duhamel
This paper proposes a lossless point cloud (PC) geometry compression method that uses neural networks to estimate the probability distribution of voxel occupancy.
2 code implementations • 20 Apr 2021 • Dat Thanh Nguyen, Maurice Quach, Giuseppe Valenzise, Pierre Duhamel
We propose a practical deep generative approach for lossless point cloud geometry compression, called MSVoxelDNN, and show that it significantly reduces the rate compared to the MPEG G-PCC codec.
1 code implementation • 25 Feb 2021 • Maurice Quach, Aladine Chetouani, Giuseppe Valenzise, Frederic Dufaux
In addition, we propose a novel truncated distance field voxel grid representation and find that it leads to sparser latent spaces and loss functions that are more correlated with perceived visual quality compared to a binary representation.
no code implementations • 1 Dec 2020 • Goluck Konuko, Giuseppe Valenzise, Stéphane Lathuilière
In this work we propose a novel deep learning approach for ultra-low bitrate video compression for video conferencing applications.
1 code implementation • 30 Nov 2020 • Dat Thanh Nguyen, Maurice Quach, Giuseppe Valenzise, Pierre Duhamel
On the one hand, octree representation can eliminate the sparsity in the point cloud.
2 code implementations • 16 Jun 2020 • Maurice Quach, Giuseppe Valenzise, Frederic Dufaux
Point clouds have been recognized as a crucial data structure for 3D content and are essential in a number of applications such as virtual and mixed reality, autonomous driving, cultural heritage, etc.
1 code implementation • 11 Feb 2020 • Maurice Quach, Giuseppe Valenzise, Frederic Dufaux
However, as this mapping process is lossy in nature, we propose several strategies to refine it so that attributes can be mapped to the 2D grid with minimal distortion.
1 code implementation • 27 Nov 2019 • Subhayan Mukherjee, Giuseppe Valenzise, Irene Cheng
However, majority of such methods either use hand-crafted features or require training on human opinion scores (supervised learning), which are difficult to obtain and standardise.
no code implementations • 12 Aug 2019 • Aakanksha Rana, Praveer Singh, Giuseppe Valenzise, Frederic Dufaux, Nikos Komodakis, Aljosa Smolic
In this paper, we address this problem by proposing a fast, parameter-free and scene-adaptable deep tone mapping operator (DeepTMO) that yields a high-resolution and high-subjective quality tone mapped output.
2 code implementations • 20 Mar 2019 • Maurice Quach, Giuseppe Valenzise, Frederic Dufaux
Efficient point cloud compression is fundamental to enable the deployment of virtual and mixed reality applications, since the number of points to code can range in the order of millions.
no code implementations • 11 Mar 2018 • Navaneeth Kamballur Kottayil, Giuseppe Valenzise, Frederic Dufaux, Irene Cheng
In this paper, we explore a different perspective, and we investigate whether it is possible to learn local distortion visibility from image quality scores.