Join the Meetup to hear talks from experts on cutting-edge topics across AI, ML, and computer vision.
Date and Location
Dec 4, 2025
5:30 – 8:30 PM
Hilton San Diego Bayfront
(Across the street from NeurIPS)
Elevation Room
1 Park Blvd
San Diego, CA
Extending RT-DETR for Line-Based Object Detection: Paddle Spine Estimation in Pickleball Serve Analysis
We present a modified vision transformer–based detection model for estimating the spine line of a pickleball paddle from video data, developed to support automated serve legality analysis and motion coaching. Building on the RT-DETR architecture, we reformulated the detection head to predict two keypoints representing the endpoints of the paddle’s longitudinal axis rather than a bounding box, enabling a general framework for regressing an arbitrary number of vertices defining lines or polygons.
To facilitate stable training, we defined a loss combining a line-IoU term with a cosine-angle regularizer that enforces geometric consistency between predicted and ground-truth orientations. Dataset curation and qualitative validation were performed using FiftyOne, allowing visual inspection of data diversity pre-training and model quality post-training. The model was trained and deployed end-to-end on the EyePop.ai platform, which provided data management, training orchestration, and model hosting for seamless integration into a third-party application performing real-time serve evaluation and feedback.
