Search Results for author:
Found 24 papers, 4 papers with code
Domain-Guided Masked Autoencoders for Unique Player Identification
We further introduce a new spatio-temporal network leveraging our novel d-MAE for unique player identification.
Distribution and Depth-Aware Transformers for 3D Human Mesh Recovery
Precise Human Mesh Recovery (HMR) with in-the-wild data is a formidable challenge and is often hindered by depth ambiguities and reduced precision.
A Unified Model Selection Technique for Spectral Clustering Based Motion Segmentation
Motion segmentation is a fundamental problem in computer vision and is crucial in various applications such as robotics, autonomous driving and action recognition.
Motion Segmentation from a Moving Monocular Camera
We then construct two robust affinity matrices representing the pairwise object motion affinities throughout the whole video using epipolar geometry and the motion information provided by optical flow.
Jersey Number Recognition using Keyframe Identification from Low-Resolution Broadcast Videos
To address these issues, we propose a robust keyframe identification module that extracts frames containing essential high-level information about the jersey number.
Mitigating Motion Blur for Robust 3D Baseball Player Pose Modeling for Pitch Analysis
The findings highlight the effectiveness of our method in mitigating the challenges posed by motion blur, thereby enhancing the overall quality of pose estimation.
H-SLAM: Hybrid Direct-Indirect Visual SLAM
The recent success of hybrid methods in monocular odometry has led to many attempts to generalize the performance gains to hybrid monocular SLAM.
Text Detection & Recognition in the Wild for Robot Localization
Our central contribution is introducing utilizing an end-to-end scene text spotting framework to adequately capture the irregular and occluded text regions in different challenging places.
Arbitrary Shape Text Detection using Transformers
At its core, our proposed method leverages a bounding box loss function that accurately measures the arbitrary detected text regions' changes in scale and aspect ratio.
Player Tracking and Identification in Ice Hockey
The player identification model further takes advantage of the available NHL game roster data to obtain a player identification accuracy of 83%.
Multi-task learning for jersey number recognition in Ice Hockey
Identifying players in sports videos by recognizing their jersey numbers is a challenging task in computer vision.
Puck localization and multi-task event recognition in broadcast hockey videos
In this paper, we introduce and implement a network for puck localization in broadcast hockey video.
Localization of Ice-Rink for Broadcast Hockey Videos
To localize the frames on the ice-rink model, a ResNet18-based regressor is implemented and trained, which regresses to four control points on the model in a frame-by-frame fashion.
Text Detection and Recognition in the Wild: A Review
Thus, unlike previous surveys in this field, the objectives of this survey are as follows: first, offering the reader not only a review on the recent advancement in scene text detection and recognition, but also presenting the results of conducting extensive experiments using a unified evaluation framework that assesses pre-trained models of the selected methods on challenging cases, and applies the same evaluation criteria on these techniques.
Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutions
Experimental results demonstrate the effectiveness of the network by obtaining a 55% average F1 score on the NHL dataset and by achieving competitive performance compared to the state of the art on the SoccerNet dataset.
Ranked #4 on
Action Spotting
on SoccerNet
Semi-supervised Anomaly Detection using AutoEncoders
But for defect detection lack of availability of a large number of anomalous instances and labelled data is a problem.
PuckNet: Estimating hockey puck location from broadcast video
The network is able to regress the puck location from broadcast hockey video clips with varying camera angles.
AnoNet: Weakly Supervised Anomaly Detection in Textured Surfaces
AnoNet can learn from a limited number of images.
Supervised Anomaly Detection
Weakly-supervised Anomaly Detection
KPTransfer: improved performance and faster convergence from keypoint subset-wise domain transfer in human pose estimation
This approach is motivated by the notion that rich contextual knowledge can be transferred between different keypoint subsets representing separate domains.
A Unified Formulation for Visual Odometry
Monocular Odometry systems can be broadly categorized as being either Direct, Indirect, or a hybrid of both.
Temporal Hockey Action Recognition via Pose and Optical Flows
Third, pose and optical flow streams are fused and passed to fully-connected layers to estimate the hockey player's action.
FDMO: Feature Assisted Direct Monocular Odometry
Visual Odometry (VO) can be categorized as being either direct or feature based.
Keyframe-based monocular SLAM: design, survey, and future directions
Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality.
