28 citations · 58 across the 12 of their papers we have counts for
7 papers · 1 filter
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…
Improving Weakly-supervised Video Instance Segmentation by Leveraging Spatio-temporal Consistency
Farnoosh Arefi, Amir M. Mansourian, Shohreh Kasaei
The performance of Video Instance Segmentation (VIS) methods has improved significantly with the advent of transformer networks. However, these networks often face challenges in tr…
SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimap
Vladimir Somers, Victor Joos, Anthony Cioppa +11
Tracking and identifying athletes on the pitch holds a central role in collecting essential insights from the game, such as estimating the total distance covered by players or unde…
Attention-guided Feature Distillation for Semantic Segmentation
Amir M. Mansourian, Arya Jalali, Rozhan Ahmadi +1
Deep learning models have achieved significant results across various computer vision tasks. However, due to the large number of parameters in these models, deploying them in real-…
Deep Spectral Improvement for Unsupervised Image Instance Segmentation
Farnoosh Arefi, Amir M. Mansourian, Shohreh Kasaei
Deep spectral methods reframe the image decomposition process as a graph partitioning task by extracting features using self-supervised learning and utilizing the Laplacian of the…
Multi-task Learning for Joint Re-identification, Team Affiliation, and Role Classification for Sports Visual Tracking
Amir M. Mansourian, Vladimir Somers, Christophe De Vleeschouwer +1
Effective tracking and re-identification of players is essential for analyzing soccer videos. But, it is a challenging task due to the non-linear motion of players, the similarity…
Rethinking RAFT for Efficient Optical Flow
Navid Eslami, Farnoosh Arefi, Amir M. Mansourian +1
Despite significant progress in deep learning-based optical flow methods, accurately estimating large displacements and repetitive patterns remains a challenge. The limitations of…