Search Results for author: Anthony Cioppa

Found 31 papers, 19 papers with code

Foundations of the Theory of Performance-Based Ranking

no code implementations5 Dec 2024 Sébastien Piérard, Anaïs Halin, Anthony Cioppa, Adrien Deliège, Marc Van Droogenbroeck

Then, we introduce a universal parametric family of scores, called ranking scores, that can be used to establish rankings satisfying our axioms, while considering application-specific preferences.

Specificity

The Tile: A 2D Map of Ranking Scores for Two-Class Classification

no code implementations5 Dec 2024 Sébastien Piérard, Anaïs Halin, Anthony Cioppa, Adrien Deliège, Marc Van Droogenbroeck

In the computer vision and machine learning communities, as well as in many other research domains, rigorous evaluation of any new method, including classifiers, is essential.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers

no code implementations5 Dec 2024 Anaïs Halin, Sébastien Piérard, Anthony Cioppa, Marc Van Droogenbroeck

In this paper, we provide a first hitchhiker's guide for understanding the performances of two-class classifiers by presenting four scenarios, each showcasing a different user profile: a theoretical analyst, a method designer, a benchmarker, and an application developer.

Semantic Segmentation

Physically Interpretable Probabilistic Domain Characterization

no code implementations22 Nov 2024 Anaïs Halin, Sébastien Piérard, Renaud Vandeghen, Benoît Gérin, Maxime Zanella, Martin Colot, Jan Held, Anthony Cioppa, Emmanuel Jean, Gianluca Bontempi, Saïd Mahmoudi, Benoît Macq, Marc Van Droogenbroeck

Characterizing domains is essential for models analyzing dynamic environments, as it allows them to adapt to evolving conditions or to hand the task over to backup systems when facing conditions outside their operational domain.

Autonomous Vehicles Domain Adaptation

3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes

1 code implementation22 Nov 2024 Jan Held, Renaud Vandeghen, Abdullah Hamdi, Adrien Deliege, Anthony Cioppa, Silvio Giancola, Andrea Vedaldi, Bernard Ghanem, Marc Van Droogenbroeck

Our results highlight the potential of 3D Convex Splatting to become the new standard for high-quality scene reconstruction and novel view synthesis.

3DGS Novel View Synthesis

Deep learning for action spotting in association football videos

no code implementations2 Oct 2024 Silvio Giancola, Anthony Cioppa, Bernard Ghanem, Marc Van Droogenbroeck

The task of action spotting consists in both identifying actions and precisely localizing them in time with a single timestamp in long, untrimmed video streams.

Action Spotting Benchmarking +3

SoccerNet 2024 Challenges Results

1 code implementation16 Sep 2024 Anthony Cioppa, Silvio Giancola, Vladimir Somers, Victor Joos, Floriane Magera, Jan Held, Seyed Abolfazl Ghasemzadeh, Xin Zhou, Karolina Seweryn, Mateusz Kowalczyk, Zuzanna Mróz, Szymon Łukasik, Michał Hałoń, Hassan Mkhallati, Adrien Deliège, Carlos Hinojosa, Karen Sanchez, Amir M. Mansourian, Pierre Miralles, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Adam Gorski, Albert Clapés, Andrei Boiarov, Anton Afanasiev, Artur Xarles, Atom Scott, Byoungkwon Lim, Calvin Yeung, Cristian Gonzalez, Dominic Rüfenacht, Enzo Pacilio, Fabian Deuser, Faisal Sami Altawijri, Francisco Cachón, Hankyul Kim, Haobo Wang, Hyeonmin Choe, Hyunwoo J Kim, Il-Min Kim, Jae-Mo Kang, Jamshid Tursunboev, Jian Yang, Jihwan Hong, JiMin Lee, Jing Zhang, Junseok Lee, Kexin Zhang, Konrad Habel, Licheng Jiao, Linyi Li, Marc Gutiérrez-Pérez, Marcelo Ortega, Menglong Li, Milosz Lopatto, Nikita Kasatkin, Nikolay Nemtsev, Norbert Oswald, Oleg Udin, Pavel Kononov, Pei Geng, Saad Ghazai Alotaibi, Sehyung Kim, Sergei Ulasen, Sergio Escalera, Shanshan Zhang, Shuyuan Yang, Sunghwan Moon, Thomas B. Moeslund, Vasyl Shandyba, Vladimir Golovkin, Wei Dai, WonTaek Chung, Xinyu Liu, Yongqiang Zhu, Youngseo Kim, Yuan Li, Yuting Yang, Yuxuan Xiao, Zehua Cheng, Zhihao LI

The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team.

Action Spotting Dense Video Captioning +2

Investigating Event-Based Cameras for Video Frame Interpolation in Sports

no code implementations2 Jul 2024 Antoine Deckyvere, Anthony Cioppa, Silvio Giancola, Bernard Ghanem, Marc Van Droogenbroeck

This first investigation underscores the practical utility of event-based cameras in producing sports slow-motion content and lays the groundwork for future research endeavors in this domain.

Video Frame Interpolation

OSL-ActionSpotting: A Unified Library for Action Spotting in Sports Videos

no code implementations1 Jul 2024 Yassine Benzakour, Bruno Cabado, Silvio Giancola, Anthony Cioppa, Bernard Ghanem, Marc Van Droogenbroeck

Action spotting is crucial in sports analytics as it enables the precise identification and categorization of pivotal moments in sports matches, providing insights that are essential for performance analysis and tactical decision-making.

Action Spotting Decision Making +1

Efficient Image Pre-Training with Siamese Cropped Masked Autoencoders

1 code implementation26 Mar 2024 Alexandre Eymaël, Renaud Vandeghen, Anthony Cioppa, Silvio Giancola, Bernard Ghanem, Marc Van Droogenbroeck

In particular, SiamMAE recently introduced a Siamese network, training a shared-weight encoder from two frames of a video with a high asymmetric masking ratio (95%).

Object Self-Supervised Learning

SoccerNet 2023 Challenges Results

2 code implementations12 Sep 2023 Anthony Cioppa, Silvio Giancola, Vladimir Somers, Floriane Magera, Xin Zhou, Hassan Mkhallati, Adrien Deliège, Jan Held, Carlos Hinojosa, Amir M. Mansourian, Pierre Miralles, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdullah Kamal, Adrien Maglo, Albert Clapés, Amr Abdelaziz, Artur Xarles, Astrid Orcesi, Atom Scott, Bin Liu, Byoungkwon Lim, Chen Chen, Fabian Deuser, Feng Yan, Fufu Yu, Gal Shitrit, Guanshuo Wang, Gyusik Choi, Hankyul Kim, Hao Guo, Hasby Fahrudin, Hidenari Koguchi, Håkan Ardö, Ibrahim Salah, Ido Yerushalmy, Iftikar Muhammad, Ikuma Uchida, Ishay Be'ery, Jaonary Rabarisoa, Jeongae Lee, Jiajun Fu, Jianqin Yin, Jinghang Xu, Jongho Nang, Julien Denize, Junjie Li, Junpei Zhang, Juntae Kim, Kamil Synowiec, Kenji Kobayashi, Kexin Zhang, Konrad Habel, Kota Nakajima, Licheng Jiao, Lin Ma, Lizhi Wang, Luping Wang, Menglong Li, Mengying Zhou, Mohamed Nasr, Mohamed Abdelwahed, Mykola Liashuha, Nikolay Falaleev, Norbert Oswald, Qiong Jia, Quoc-Cuong Pham, Ran Song, Romain Hérault, Rui Peng, Ruilong Chen, Ruixuan Liu, Ruslan Baikulov, Ryuto Fukushima, Sergio Escalera, Seungcheon Lee, Shimin Chen, Shouhong Ding, Taiga Someya, Thomas B. Moeslund, Tianjiao Li, Wei Shen, Wei zhang, Wei Li, Wei Dai, Weixin Luo, Wending Zhao, Wenjie Zhang, Xinquan Yang, Yanbiao Ma, Yeeun Joo, Yingsen Zeng, Yiyang Gan, Yongqiang Zhu, Yujie Zhong, Zheng Ruan, Zhiheng Li, Zhijian Huang, Ziyu Meng

More information on the tasks, challenges, and leaderboards are available on https://www. soccer-net. org.

Action Spotting Camera Calibration +4

SoccerNet-Caption: Dense Video Captioning for Soccer Broadcasts Commentaries

2 code implementations10 Apr 2023 Hassan Mkhallati, Anthony Cioppa, Silvio Giancola, Bernard Ghanem, Marc Van Droogenbroeck

By providing broadcasters with a tool to summarize the content of their video with the same level of engagement as a live game, our method could help satisfy the needs of the numerous fans who follow their team but cannot necessarily watch the live game.

Dense Video Captioning

VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Views

1 code implementation10 Apr 2023 Jan Held, Anthony Cioppa, Silvio Giancola, Abdullah Hamdi, Bernard Ghanem, Marc Van Droogenbroeck

The Video Assistant Referee (VAR) has revolutionized association football, enabling referees to review incidents on the pitch, make informed decisions, and ensure fairness.

Decision Making Fairness

Towards Active Learning for Action Spotting in Association Football Videos

no code implementations9 Apr 2023 Silvio Giancola, Anthony Cioppa, Julia Georgieva, Johsan Billingham, Andreas Serner, Kerry Peek, Bernard Ghanem, Marc Van Droogenbroeck

In this paper, we propose an active learning framework that selects the most informative video samples to be annotated next, thus drastically reducing the annotation effort and accelerating the training of action spotting models to reach the highest accuracy at a faster pace.

Action Spotting Active Learning

Online Distillation with Continual Learning for Cyclic Domain Shifts

1 code implementation3 Apr 2023 Joachim Houyon, Anthony Cioppa, Yasir Ghunaim, Motasem Alfarra, Anaïs Halin, Maxim Henry, Bernard Ghanem, Marc Van Droogenbroeck

In this paper, we propose a solution to this issue by leveraging the power of continual learning methods to reduce the impact of domain shifts.

Autonomous Driving Continual Learning

Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance

1 code implementation18 Nov 2022 Sébastien Piérard, Anthony Cioppa, Anaïs Halin, Renaud Vandeghen, Maxime Zanella, Benoît Macq, Saïd Mahmoudi, Marc Van Droogenbroeck

In this paper, we define a probabilistic framework and present a formal proof of an algorithm for the unsupervised many-to-infinity domain adaptation of posteriors.

Bayesian Inference Domain Adaptation +1

SoccerNet 2022 Challenges Results

7 code implementations5 Oct 2022 Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.

Action Spotting Camera Calibration +3

Semi-Supervised Training to Improve Player and Ball Detection in Soccer

1 code implementation14 Apr 2022 Renaud Vandeghen, Anthony Cioppa, Marc Van Droogenbroeck

More precisely, we design a teacher-student approach in which the teacher produces surrogate annotations on the unlabeled data to be used later for training a student which has the same architecture as the teacher.

SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos

no code implementations14 Apr 2022 Anthony Cioppa, Silvio Giancola, Adrien Deliege, Le Kang, Xin Zhou, Zhiyu Cheng, Bernard Ghanem, Marc Van Droogenbroeck

Tracking objects in soccer videos is extremely important to gather both player and team statistics, whether it is to estimate the total distance run, the ball possession or the team formation.

Benchmarking Multiple Object Tracking

Ghost Loss to Question the Reliability of Training Data

no code implementations3 Sep 2021 Adrien Deliège, Anthony Cioppa, Marc Van Droogenbroeck

For that purpose, we introduce the notion of ghost loss, which can be seen as a regular loss that is zeroed out for some predicted values in a deterministic way and that allows the network to choose an alternative to the given label without being penalized.

Image Classification

Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting

no code implementations19 Apr 2021 Anthony Cioppa, Adrien Deliège, Floriane Magera, Silvio Giancola, Olivier Barnich, Bernard Ghanem, Marc Van Droogenbroeck

Specifically, we distill a powerful commercial calibration tool in a recent neural network architecture on the large-scale SoccerNet dataset, composed of untrimmed broadcast videos of 500 soccer games.

Action Spotting Camera Calibration +1

SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos

4 code implementations26 Nov 2020 Adrien Deliège, Anthony Cioppa, Silvio Giancola, Meisam J. Seikavandi, Jacob V. Dueholm, Kamal Nasrollahi, Bernard Ghanem, Thomas B. Moeslund, Marc Van Droogenbroeck

In this work, we propose SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production.

Action Spotting Boundary Detection +5

Multimodal and multiview distillation for real-time player detection on a football field

1 code implementation16 Apr 2020 Anthony Cioppa, Adrien Deliège, Noor Ul Huda, Rikke Gade, Marc Van Droogenbroeck, Thomas B. Moeslund

As an alternative, we developed a system that detects players from a unique cheap and wide-angle fisheye camera assisted by a single narrow-angle thermal camera.

Data Augmentation Knowledge Distillation +1

Real-Time Semantic Background Subtraction

1 code implementation12 Feb 2020 Anthony Cioppa, Marc Van Droogenbroeck, Marc Braham

Semantic background subtraction SBS has been shown to improve the performance of most background subtraction algorithms by combining them with semantic information, derived from a semantic segmentation network.

Semantic Segmentation

HitNet: a neural network with capsules embedded in a Hit-or-Miss layer, extended with hybrid data augmentation and ghost capsules

1 code implementation18 Jun 2018 Adrien Deliège, Anthony Cioppa, Marc Van Droogenbroeck

In this paper, we show how to redesign a simple network to reach excellent performances, which are better than the results reproduced with CapsNet on several datasets, by replacing a layer with a Hit-or-Miss layer.

Data Augmentation

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