Search Results for author:
Found 47 papers, 29 papers with code
Action Anticipation from SoccerNet Football Video Broadcasts
In this work, we introduce the task of action anticipation for football broadcast videos, which consists in predicting future actions in unobserved future frames, within a five- or ten-second anticipation window.
Spiideo SoccerNet SynLoc: Single Frame World Coordinate Athlete Detection and Localization with Synthetic Data
To promote research that can take benefits of such cameras and produce more precise pitch locations, we introduce the Spiideo SoccerNet SynLoc dataset.
Ranked #1 on
3D Object Detection
on Spiideo SoccerNet SynLoc
OpenTAD: A Unified Framework and Comprehensive Study of Temporal Action Detection
Temporal action detection (TAD) is a fundamental video understanding task that aims to identify human actions and localize their temporal boundaries in videos.
3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes
Our results highlight the potential of 3D Convex Splatting to become the new standard for high-quality scene reconstruction and novel view synthesis.
Deep learning for action spotting in association football videos
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.
SoccerNet 2024 Challenges Results
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team.
TrackNeRF: Bundle Adjusting NeRF from Sparse and Noisy Views via Feature Tracks
Neural radiance fields (NeRFs) generally require many images with accurate poses for accurate novel view synthesis, which does not reflect realistic setups where views can be sparse and poses can be noisy.
Towards AI-Powered Video Assistant Referee System (VARS) for Association Football
VARS sets a new state-of-the-art on the SoccerNet-MVFoul dataset, a multi-view video dataset of football fouls.
Hybrid Structure-from-Motion and Camera Relocalization for Enhanced Egocentric Localization
We built our pipeline EgoLoc-v1, mainly inspired by EgoLoc.
Investigating Event-Based Cameras for Video Frame Interpolation in Sports
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.
OSL-ActionSpotting: A Unified Library for Action Spotting in Sports Videos
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.
SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset
The application of Automatic Speech Recognition (ASR) technology in soccer offers numerous opportunities for sports analytics.
SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimap
This tracking and identification process is crucial for reconstructing the game state, defined by the athletes' positions and identities on a 2D top-view of the pitch, (i. e. a minimap).
Ranked #1 on
Game State Reconstruction
on SoccerNet-GSR
X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Model
The rapid advancement of artificial intelligence has led to significant improvements in automated decision-making.
Efficient Image Pre-Training with Siamese Cropped Masked Autoencoders
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%).
Artificial intelligence optical hardware empowers high-resolution hyperspectral video understanding at 1.2 Tb/s
The technology platform combines artificial intelligence hardware, processing information optically, with state-of-the-art machine vision networks, resulting in a data processing speed of 1. 2 Tb/s with hundreds of frequency bands and megapixel spatial resolution at video rates.
SoccerNet 2023 Challenges Results
More information on the tasks, challenges, and leaderboards are available on https://www. soccer-net. org.
Learning Semantic Segmentation with Query Points Supervision on Aerial Images
In this work, we present a weakly supervised learning algorithm to train semantic segmentation algorithms that only rely on query point annotations instead of full mask labels.
SoccerNet-Caption: Dense Video Captioning for Soccer Broadcasts Commentaries
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.
VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Views
The Video Assistant Referee (VAR) has revolutionized association football, enabling referees to review incidents on the pitch, make informed decisions, and ensure fairness.
Towards Active Learning for Action Spotting in Association Football Videos
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.
MVTN: Learning Multi-View Transformations for 3D Understanding
Multi-view projection techniques have shown themselves to be highly effective in achieving top-performing results in the recognition of 3D shapes.
EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries
Yet, we point out that the low number of camera poses caused by camera re-localization from previous VQ3D methods severally hinders their overall success rate.
SegNeRF: 3D Part Segmentation with Neural Radiance Fields
The predicted semantic fields allow SegNeRF to achieve an average mIoU of $\textbf{30. 30%}$ for 2D novel view segmentation, and $\textbf{37. 46%}$ for 3D part segmentation, boasting competitive performance against point-based methods by using only a few posed images.
Estimating more camera poses for ego-centric videos is essential for VQ3D
Visual queries 3D localization (VQ3D) is a task in the Ego4D Episodic Memory Benchmark.
SoccerNet 2022 Challenges Results
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos
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.
3DeformRS: Certifying Spatial Deformations on Point Clouds
In this work, we propose 3DeformRS, a method to certify the robustness of point cloud Deep Neural Networks (DNNs) against real-world deformations.
Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders
Hyperspectral imaging has attracted significant attention to identify spectral signatures for image classification and automated pattern recognition in computer vision.
MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions
The recent and increasing interest in video-language research has driven the development of large-scale datasets that enable data-intensive machine learning techniques.
Ranked #4 on
Natural Language Moment Retrieval
on MAD
Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding
To this end, we introduce the concept of the multi-view point cloud (Voint cloud), representing each 3D point as a set of features extracted from several view-points.
SCTN: Sparse Convolution-Transformer Network for Scene Flow Estimation
We propose a novel scene flow estimation approach to capture and infer 3D motions from point clouds.
Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting
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.
Temporally-Aware Feature Pooling for Action Spotting in Soccer Broadcasts
In this paper, we focus our analysis on action spotting in soccer broadcast, which consists in temporally localizing the main actions in a soccer game.
Ranked #7 on
Action Spotting
on SoccerNet-v2
(Average-mAP metric)
SALA: Soft Assignment Local Aggregation for Parameter Efficient 3D Semantic Segmentation
Since it is learnable, this mapping is allowed to be different per layer instead of being applied uniformly throughout the depth of the network.
MVTN: Multi-View Transformation Network for 3D Shape Recognition
MVTN exhibits clear performance gains in the tasks of 3D shape classification and 3D shape retrieval without the need for extra training supervision.
Ranked #1 on
3D Object Retrieval
on ModelNet40
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
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.
Ranked #1 on
Camera shot segmentation
on SoccerNet-v2
TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks
Extensive experiments show that using features trained with our novel pretraining strategy significantly improves the performance of recent state-of-the-art methods on three tasks: Temporal Action Localization, Action Proposal Generation, and Dense Video Captioning.
LC-NAS: Latency Constrained Neural Architecture Search for Point Cloud Networks
In this paper, we introduce a new NAS framework, dubbed LC-NAS, where we search for point cloud architectures that are constrained to a target latency.
A Context-Aware Loss Function for Action Spotting in Soccer Videos
We benchmark our loss on a large dataset of soccer videos, SoccerNet, and achieve an improvement of 12. 8% over the baseline.
Ranked #3 on
Action Spotting
on SoccerNet
PointRGCN: Graph Convolution Networks for 3D Vehicles Detection Refinement
We integrate residual GCNs in a two-stage 3D object detection pipeline, where 3D object proposals are refined using a novel graph representation.
Ranked #15 on
3D Object Detection
on KITTI Cars Hard
Efficient Bird Eye View Proposals for 3D Siamese Tracking
Successively, we refine our selection of 3D object candidates by exploiting the similarity capability of a 3D Siamese network.
Leveraging Shape Completion for 3D Siamese Tracking
We design a Siamese tracker that encodes model and candidate shapes into a compact latent representation.
SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos
A total of 6, 637 temporal annotations are automatically parsed from online match reports at a one minute resolution for three main classes of events (Goal, Yellow/Red Card, and Substitution).
Ranked #6 on
Action Spotting
on SoccerNet
TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild
In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild.
Integration of Absolute Orientation Measurements in the KinectFusion Reconstruction pipeline
We also present a technique to filter the pairs of 3D matched points based on the distribution of their distances.
A Solution for Crime Scene Reconstruction using Time-of-Flight Cameras
In this work, we propose a method for three-dimensional (3D) reconstruction of wide crime scene, based on a Simultaneous Localization and Mapping (SLAM) approach.
