27 citations · 39 across the 12 of their papers we have counts for
14 papers
Evaluating deep tracking models for player tracking in broadcast ice hockey video
Kanav Vats, Mehrnaz Fani, David A. Clausi +1
Tracking and identifying players is an important problem in computer vision based ice hockey analytics. Player tracking is a challenging problem since the motion of players in hock…
Player Tracking and Identification in Ice Hockey
Kanav Vats, Pascale Walters, Mehrnaz Fani +2
Tracking and identifying players is a fundamental step in computer vision-based ice hockey analytics. The data generated by tracking is used in many other downstream tasks, such as…
Ice hockey player identification via transformers and weakly supervised learning
Kanav Vats, William McNally, Pascale Walters +2
Identifying players in video is a foundational step in computer vision-based sports analytics. Obtaining player identities is essential for analyzing the game and is used in downst…
Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation
William McNally, Kanav Vats, Alexander Wong +1
In keypoint estimation tasks such as human pose estimation, heatmap-based regression is the dominant approach despite possessing notable drawbacks: heatmaps intrinsically suffer fr…
Multi-task learning for jersey number recognition in Ice Hockey
Kanav Vats, Mehrnaz Fani, David A. Clausi +1
Identifying players in sports videos by recognizing their jersey numbers is a challenging task in computer vision. We have designed and implemented a multi-task learning network fo…
Puck localization and multi-task event recognition in broadcast hockey videos
Kanav Vats, Mehrnaz Fani, David A. Clausi +1
Puck localization is an important problem in ice hockey video analytics useful for analyzing the game, determining play location, and assessing puck possession. The problem is chal…
DeepDarts: Modeling Keypoints as Objects for Automatic Scorekeeping in Darts using a Single Camera
William McNally, Pascale Walters, Kanav Vats +2
Existing multi-camera solutions for automatic scorekeeping in steel-tip darts are very expensive and thus inaccessible to most players. Motivated to develop a more accessible low-c…
EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using Accelerated Neuroevolution with Weight Transfer
William McNally, Kanav Vats, Alexander Wong +1
Neural architecture search has proven to be highly effective in the design of efficient convolutional neural networks that are better suited for mobile deployment than hand-designe…
Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutions
Kanav Vats, Mehrnaz Fani, Pascale Walters +2
In problems such as sports video analytics, it is difficult to obtain accurate frame level annotations and exact event duration because of the lengthy videos and sheer volume of vi…
PuckNet: Estimating hockey puck location from broadcast video
Kanav Vats, William McNally, Chris Dulhanty +3
Puck location in ice hockey is essential for hockey analysts for determining the location of play and analyzing game events. However, because of the difficulty involved in obtainin…
Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning
Devinder Kumar, Ibrahim Ben-Daya, Kanav Vats +3
In this study, we propose the leveraging of interpretability for tasks beyond purely the purpose of explainability. In particular, this study puts forward a novel strategy for leve…
KPTransfer: improved performance and faster convergence from keypoint subset-wise domain transfer in human pose estimation
Kanav Vats, Helmut Neher, Alexander Wong +2
In this paper, we present a novel approach called KPTransfer for improving modeling performance for keypoint detection deep neural networks via domain transfer between different ke…
GolfDB: A Video Database for Golf Swing Sequencing
William McNally, Kanav Vats, Tyler Pinto +3
The golf swing is a complex movement requiring considerable full-body coordination to execute proficiently. As such, it is the subject of frequent scrutiny and extensive biomechani…
Temporal Hockey Action Recognition via Pose and Optical Flows
Zixi Cai, Helmut Neher, Kanav Vats +2
Recognizing actions in ice hockey using computer vision poses challenges due to bulky equipment and inadequate image quality. A novel two-stream framework has been designed to impr…