Search Results for author: Frederic Dufaux

Found 8 papers, 5 papers with code

A deep perceptual metric for 3D point clouds

1 code implementation25 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.

Improved Deep Point Cloud Geometry Compression

2 code implementations16 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.

Autonomous Driving Mixed Reality

Folding-based compression of point cloud attributes

1 code implementation11 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.

Representation Learning

Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image Classification

1 code implementation4 Oct 2019 Florent Chiaroni, Ghazaleh Khodabandelou, Mohamed-Cherif Rahal, Nicolas Hueber, Frederic Dufaux

In this manner, the discriminator is constrained to request the generator to converge towards the unlabeled samples distribution while diverging from the positive samples distribution.

General Classification Image Classification

Deep Tone Mapping Operator for High Dynamic Range Images

no code implementations12 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.

Tone Mapping

Learning Convolutional Transforms for Lossy Point Cloud Geometry Compression

2 code implementations20 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.

Mixed Reality Quantization

Learning Local Distortion Visibility From Image Quality Data-sets

no code implementations11 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.

Local Distortion

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