8 citations · 9 across the 17 of their papers we have counts for
20 papers
Benchmarking Multimodal Large Language Models for Zero-Shot Human-Object Interaction
Oriol Rabasseda, Zenjie Li, Kamal Nasrollahi +1
Multimodal Large Language Models (MLLMs) have demonstrated strong zero-shot reasoning across diverse domains, but their potential for Human-Object Interaction (HOI) remains unexplo…
MVTrack: Ultrafast Appearance-Free Moving Object Tracking from Compressed Bitstreams
Iñaki Erregue, Kamal Nasrollahi, Sergio Escalera
Deploying modern video trackers at scale is bottlenecked by the computational cost of RGB-based object detectors. To this end, we present MVTrack, an ultrafast tracker for moving o…
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…
A Hyperbolic Perspective on Hierarchical Structure in Object-Centric Scene Representations
Neelu Madan, Àlex Pujol, Andreas Møgelmose +4
Slot attention has emerged as a powerful framework for unsupervised object-centric learning, decomposing visual scenes into a small set of compact vector representations called \em…
AdaSpot: Spend Resolution Where It Matters for Precise Event Spotting
Artur Xarles, Sergio Escalera, Thomas B. Moeslund +1
Precise Event Spotting aims to localize fast-paced actions or events in videos with high temporal precision, a key task for applications in sports analytics, robotics, and autonomo…
SOVABench: A Vehicle Surveillance Action Retrieval Benchmark for Multimodal Large Language Models
Oriol Rabasseda, Zenjie Li, Kamal Nasrollahi +1
Automatic identification of events and recurrent behavior analysis are critical for video surveillance. However, most existing content-based video retrieval benchmarks focus on sce…
PrismVAU: Prompt-Refined Inference System for Multimodal Video Anomaly Understanding
Iñaki Erregue, Kamal Nasrollahi, Sergio Escalera
Video Anomaly Understanding (VAU) extends traditional Video Anomaly Detection (VAD) by not only localizing anomalies but also describing and reasoning about their context. Existing…
SoccerNet 2025 Challenges Results
Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115
The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…
COOkeD: Ensemble-based OOD detection in the era of zero-shot CLIP
Galadrielle Humblot-Renaux, Gianni Franchi, Sergio Escalera +1
Out-of-distribution (OOD) detection is an important building block in trustworthy image recognition systems as unknown classes may arise at test-time. OOD detection methods typical…
Sparse-Dense Side-Tuner for efficient Video Temporal Grounding
David Pujol-Perich, Sergio Escalera, Albert Clapés
Video Temporal Grounding (VTG) involves Moment Retrieval (MR) and Highlight Detection (HD) based on textual queries. For this, most methods rely solely on final-layer features of f…
Action Anticipation from SoccerNet Football Video Broadcasts
Mohamad Dalal, Artur Xarles, Anthony Cioppa +6
Artificial intelligence has revolutionized the way we analyze sports videos, whether to understand the actions of games in long untrimmed videos or to anticipate the player's motio…
Machine Unlearning in Hyperbolic vs. Euclidean Multimodal Contrastive Learning: Adapting Alignment Calibration to MERU
Àlex Pujol Vidal, Sergio Escalera, Kamal Nasrollahi +1
Machine unlearning methods have become increasingly important for selective concept removal in large pre-trained models. While recent work has explored unlearning in Euclidean cont…
Action Valuation in Sports: A Survey
Artur Xarles, Sergio Escalera, Thomas B. Moeslund +1
Action Valuation (AV) has emerged as a key topic in Sports Analytics, offering valuable insights by assigning scores to individual actions based on their contribution to desired ou…
YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID
Iñaki Erregue, Kamal Nasrollahi, Sergio Escalera
We introduce YOLO11-JDE, a fast and accurate multi-object tracking (MOT) solution that combines real-time object detection with self-supervised Re-Identification (Re-ID). By incorp…
Multimodal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds
Simon B. Jensen, Stefan Oehmcke, Andreas Møgelmose +4
Assessment of forest biodiversity is crucial for ecosystem management and conservation. While traditional field surveys provide high-quality assessments, they are labor-intensive a…
Verifying Machine Unlearning with Explainable AI
Àlex Pujol Vidal, Anders S. Johansen, Mohammad N. S. Jahromi +3
We investigate the effectiveness of Explainable AI (XAI) in verifying Machine Unlearning (MU) within the context of harbor front monitoring, focusing on data privacy and regulatory…
Agglomerative Token Clustering
Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor +1
We present Agglomerative Token Clustering (ATC), a novel token merging method that consistently outperforms previous token merging and pruning methods across image classification,…
SoccerNet 2024 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +81
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple t…
T-DEED: Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in Sports Videos
Artur Xarles, Sergio Escalera, Thomas B. Moeslund +1
In this paper, we introduce T-DEED, a Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in sports videos. T-DEED addresses multiple challenges in the ta…
A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?
Galadrielle Humblot-Renaux, Sergio Escalera, Thomas B. Moeslund
The ability to detect unfamiliar or unexpected images is essential for safe deployment of computer vision systems. In the context of classification, the task of detecting images ou…