188 citations · 418 across the 13 of their papers we have counts for
17 papers
Predictive Coding For Animation-Based Video Compression
Goluck Konuko, Stéphane Lathuilière, Giuseppe Valenzise
We address the problem of efficiently compressing video for conferencing-type applications. We build on recent approaches based on image animation, which can achieve good reconstru…
Quality evaluation of point clouds: a novel no-reference approach using transformer-based architecture
Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise +1
With the increased interest in immersive experiences, point cloud came to birth and was widely adopted as the first choice to represent 3D media. Besides several distortions that c…
BASICS: Broad quality Assessment of Static point clouds In Compression Scenarios
Ali Ak, Emin Zerman, Maurice Quach +4
Point clouds have become increasingly prevalent in representing 3D scenes within virtual environments, alongside 3D meshes. Their ease of capture has facilitated a wide array of ap…
PCQA-GRAPHPOINT: Efficients Deep-Based Graph Metric For Point Cloud Quality Assessment
Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise +1
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…
A Hybrid Deep Animation Codec for Low-bitrate Video Conferencing
Goluck Konuko, Stéphane Lathuilière, Giuseppe Valenzise
Deep generative models, and particularly facial animation schemes, can be used in video conferencing applications to efficiently compress a video through a sparse set of keypoints,…
Lossless Coding of Point Cloud Geometry using a Deep Generative Model
Dat Thanh Nguyen, Maurice Quach, Giuseppe Valenzise +1
This paper proposes a lossless point cloud (PC) geometry compression method that uses neural networks to estimate the probability distribution of voxel occupancy. First, to take in…
Multiscale deep context modeling for lossless point cloud geometry compression
Dat Thanh Nguyen, Maurice Quach, Giuseppe Valenzise +1
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 MP…
A deep perceptual metric for 3D point clouds
Maurice Quach, Aladine Chetouani, Giuseppe Valenzise +1
Point clouds are essential for storage and transmission of 3D content. As they can entail significant volumes of data, point cloud compression is crucial for practical usage. Recen…
Ultra-low bitrate video conferencing using deep image animation
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. To address the shortcomings of current video com…
Learning-based lossless compression of 3D point cloud geometry
Dat Thanh Nguyen, Maurice Quach, Giuseppe Valenzise +1
This paper presents a learning-based, lossless compression method for static point cloud geometry, based on context-adaptive arithmetic coding. Unlike most existing methods working…
Improved Deep Point Cloud Geometry Compression
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, cu…
Folding-based compression of point cloud attributes
Maurice Quach, Giuseppe Valenzise, Frederic Dufaux
Existing techniques to compress point cloud attributes leverage either geometric or video-based compression tools. We explore a radically different approach inspired by recent adva…
Potential of deep features for opinion-unaware, distortion-unaware, no-reference image quality assessment
Subhayan Mukherjee, Giuseppe Valenzise, Irene Cheng
Image Quality Assessment algorithms predict a quality score for a pristine or distorted input image, such that it correlates with human opinion. Traditional methods required a non-…
Deep Tone Mapping Operator for High Dynamic Range Images
Aakanksha Rana, Praveer Singh, Giuseppe Valenzise +3
A computationally fast tone mapping operator (TMO) that can quickly adapt to a wide spectrum of high dynamic range (HDR) content is quintessential for visualization on varied low d…
Learning Convolutional Transforms for Lossy Point Cloud Geometry Compression
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 mi…
Learning Local Distortion Visibility From Image Quality Data-sets
Navaneeth Kamballur Kottayil, Giuseppe Valenzise, Frederic Dufaux +1
Accurate prediction of local distortion visibility thresholds is critical in many image and video processing applications. Existing methods require an accurate modeling of the huma…
Blind High Dynamic Range Quality estimation by disentangling perceptual and noise features in images
Navaneeth Kamballur Kottayil, Giuseppe Valenzise, Frederic Dufaux +1
Assessing the visual quality of High Dynamic Range (HDR) images is an unexplored and an interesting research topic that has become relevant with the current boom in HDR technology.…