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20172023
most citedSoccerNet 2023 Challenges Results

28 citations · 47 across the 8 of their papers we have counts for

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7 papers · 1 filter

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★ 2 cited

Self-Supervised Pre-training of Vision Transformers for Dense Prediction Tasks

Jaonary Rabarisoa, Valentin Belissen, Florian Chabot +1

We present a new self-supervised pre-training of Vision Transformers for dense prediction tasks. It is based on a contrastive loss across views that compares pixel-level representa…

cs.CV2022★ 9 cited

End-to-end Person Search Sequentially Trained on Aggregated Dataset

Angelique Loesch, Jaonary Rabarisoa, Romaric Audigier

In video surveillance applications, person search is a challenging task consisting in detecting people and extracting features from their silhouette for re-identification (re-ID) p…

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.CV2017

Deep MANTA: A Coarse-to-fine Many-Task Network for joint 2D and 3D vehicle analysis from monocular image

Florian Chabot, Mohamed Chaouch, Jaonary Rabarisoa +2

In this paper, we present a novel approach, called Deep MANTA (Deep Many-Tasks), for many-task vehicle analysis from a given image. A robust convolutional network is introduced for…