activity
20202023
most citedSoccerNet 2022 Challenges Results

37 citations · 84 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2023

COMEDIAN: Self-Supervised Learning and Knowledge Distillation for Action Spotting using Transformers

Julien Denize, Mykola Liashuha, Jaonary Rabarisoa +2

We present COMEDIAN, a novel pipeline to initialize spatiotemporal transformers for action spotting, which involves self-supervised learning and knowledge distillation. Action spot…

cs.CV2023★ 28 cited

SoccerNet 2023 Challenges Results

Anthony Cioppa, Silvio Giancola, Vladimir Somers +99

The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vi…

cs.CV2022★ 8 cited

Similarity Contrastive Estimation for Image and Video Soft Contrastive Self-Supervised Learning

Julien Denize, Jaonary Rabarisoa, Astrid Orcesi +1

Contrastive representation learning has proven to be an effective self-supervised learning method for images and videos. Most successful approaches are based on Noise Contrastive E…

cs.CV2022★ 37 cited

SoccerNet 2022 Challenges Results

Silvio Giancola, Anthony Cioppa, Adrien Deliège +91

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…

cs.CV2022★ 9 cited

KaliCalib: A Framework for Basketball Court Registration

Adrien Maglo, Astrid Orcesi, Quoc Cuong Pham

Tracking the players and the ball in team sports is key to analyse the performance or to enhance the game watching experience with augmented reality. When the only sources for this…

cs.CV2022

Efficient tracking of team sport players with few game-specific annotations

Adrien Maglo, Astrid Orcesi, Quoc-Cuong Pham

One of the requirements for team sports analysis is to track and recognize players. Many tracking and reidentification methods have been proposed in the context of video surveillan…

cs.CV2022★ 2 cited

Detecting Human-to-Human-or-Object (H2O) Interactions with DIABOLO

Astrid Orcesi, Romaric Audigier, Fritz Poka Toukam +1

Detecting human interactions is crucial for human behavior analysis. Many methods have been proposed to deal with Human-to-Object Interaction (HOI) detection, i.e., detecting in an…

cs.CV2021

Similarity Contrastive Estimation for Self-Supervised Soft Contrastive Learning

Julien Denize, Jaonary Rabarisoa, Astrid Orcesi +2

Contrastive representation learning has proven to be an effective self-supervised learning method. Most successful approaches are based on Noise Contrastive Estimation (NCE) and us…

cs.CV2020

Classifying All Interacting Pairs in a Single Shot

Sanaa Chafik, Astrid Orcesi, Romaric Audigier +1

In this paper, we introduce a novel human interaction detection approach, based on CALIPSO (Classifying ALl Interacting Pairs in a Single shOt), a classifier of human-object intera…