41 citations · 71 across the 10 of their papers we have counts for
13 papers
Advancing Video-Text Pretraining with Multi-View Captions
Fida M. Thoker, Renaud Vandeghen, Karen Sanchez +2
Video-text pretraining has achieved remarkable progress through the scaling of models and datasets, yet the quality of language supervision remains underexplored. Existing web-scal…
SoccerNet 2026 Challenges Results
Anthony Cioppa, Silvio Giancola, Håkan Ardö +102
The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in sports video underst…
Event Detection in Videos: A Framework for the Development of New Methods
Anastasia Zakharova, Thierry Bouwmans, Anthony Cioppa +13
Event detection tasks in videos, the most important aspect of video surveillance, aim to detect events either at the pixel-level, frame-level, or clip-level. Plenty of methods inte…
TrackMAE: Video Representation Learning via Track Mask and Predict
Renaud Vandeghen, Fida Mohammad Thoker, Marc Van Droogenbroeck +1
Masked video modeling (MVM) has emerged as a simple and scalable self-supervised pretraining paradigm, but only encodes motion information implicitly, limiting the encoding of temp…
MeshSplatting: Differentiable Rendering with Opaque Meshes
Jan Held, Sanghyun Son, Renaud Vandeghen +7
Primitive-based splatting methods like 3D Gaussian Splatting have revolutionized novel view synthesis with real-time rendering. However, their point-based representations remain in…
Triangle Splatting+: Differentiable Rendering with Opaque Triangles
Jan Held, Renaud Vandeghen, Sanghyun Son +6
Reconstructing 3D scenes and synthesizing novel views has seen rapid progress in recent years. Neural Radiance Fields demonstrated that continuous volumetric radiance fields can ac…
Triangle Splatting for Real-Time Radiance Field Rendering
Jan Held, Renaud Vandeghen, Adrien Deliege +7
The field of computer graphics was revolutionized by models such as Neural Radiance Fields and 3D Gaussian Splatting, displacing triangles as the dominant representation for photog…
Physically Interpretable Probabilistic Domain Characterization
Anaïs Halin, Sébastien Piérard, Renaud Vandeghen +10
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 fac…
3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes
Jan Held, Renaud Vandeghen, Abdullah Hamdi +6
Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes wi…
Efficient Image Pre-Training with Siamese Cropped Masked Autoencoders
Alexandre Eymaël, Renaud Vandeghen, Anthony Cioppa +3
Self-supervised pre-training of image encoders is omnipresent in the literature, particularly following the introduction of Masked autoencoders (MAE). Current efforts attempt to le…
Adaptive Self-Training for Object Detection
Renaud Vandeghen, Gilles Louppe, Marc Van Droogenbroeck
Deep learning has emerged as an effective solution for solving the task of object detection in images but at the cost of requiring large labeled datasets. To mitigate this cost, se…
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance
Sébastien Piérard, Anthony Cioppa, Anaïs Halin +5
Various tasks encountered in real-world surveillance can be addressed by determining posteriors (e.g. by Bayesian inference or machine learning), based on which critical decisions…
Semi-Supervised Training to Improve Player and Ball Detection in Soccer
Renaud Vandeghen, Anthony Cioppa, Marc Van Droogenbroeck
Accurate player and ball detection has become increasingly important in recent years for sport analytics. As most state-of-the-art methods rely on training deep learning networks i…