no code implementations • 22 Nov 2021 • Kanav Vats, William McNally, Pascale Walters, David A. Clausi, John S. Zelek
Obtaining player identities is essential for analyzing the game and is used in downstream tasks such as game event recognition.
Optical Character Recognition Optical Character Recognition (OCR) +3
1 code implementation • 16 Nov 2021 • William McNally, Kanav Vats, Alexander Wong, John McPhee
In keypoint estimation tasks such as human pose estimation, heatmap-based regression is the dominant approach despite possessing notable drawbacks: heatmaps intrinsically suffer from quantization error and require excessive computation to generate and post-process.
Ranked #9 on Pose Estimation on CrowdPose
1 code implementation • 20 May 2021 • William McNally, Pascale Walters, Kanav Vats, Alexander Wong, John McPhee
In the primary dataset containing 15k images captured from a face-on view of the dartboard using a smartphone, DeepDarts predicted the total score correctly in 94. 7% of the test images.
1 code implementation • 17 Nov 2020 • William McNally, Kanav Vats, Alexander Wong, John McPhee
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-designed networks.
Ranked #1 on Multi-Person Pose Estimation on MS COCO (Validation AP metric)
no code implementations • 11 Dec 2019 • Kanav Vats, William McNally, Chris Dulhanty, Zhong Qiu Lin, David A. Clausi, John Zelek
The network is able to regress the puck location from broadcast hockey video clips with varying camera angles.
1 code implementation • 15 Mar 2019 • William McNally, Kanav Vats, Tyler Pinto, Chris Dulhanty, John McPhee, Alexander Wong
The golf swing is a complex movement requiring considerable full-body coordination to execute proficiently.
no code implementations • 26 Feb 2019 • William McNally, Alexander Wong, John McPhee
As such, there has been recent interest on human action recognition using low-cost, readily-available RGB cameras via deep convolutional neural networks.
Ranked #5 on Multimodal Activity Recognition on UTD-MHAD