no code implementations • 4 Jan 2018 • Anurag Ghosh, C. V. Jawahar
In this paper, we demonstrate a score based indexing approach for tennis videos.
no code implementations • 23 Dec 2017 • Anurag Ghosh, Suriya Singh, C. V. Jawahar
Sports video data is recorded for nearly every major tournament but remains archived and inaccessible to large scale data mining and analytics.
no code implementations • 4 Oct 2022 • Anurag Ghosh, Srinivasan Iyengar, Stephen Lee, Anuj Rathore, Venkat N Padmanabhan
In this work, we develop REACT, a framework that leverages cloud resources to execute large DNN models with higher accuracy to improve the accuracy of models running on edge devices.
no code implementations • CVPR 2023 • Anurag Ghosh, N. Dinesh Reddy, Christoph Mertz, Srinivasa G. Narasimhan
For autonomous navigation, using the same detector and scale, our approach improves detection rate by +4. 1 $AP_{S}$ or +39% and in real-time performance by +5. 3 $sAP_{S}$ or +63% for small objects over state-of-the-art (SOTA).
no code implementations • 16 Jun 2023 • Anirudha Ramesh, Anurag Ghosh, Christoph Mertz, Jeff Schneider
Our Almost Unsupervised Domain Adaptation (AUDA) framework, a label-efficient semi-supervised approach for robotic scenarios -- employs Source Preparation (SP), Unsupervised Domain Adaptation (UDA) and Supervised Alignment (SA) from limited labeled data.
no code implementations • 19 Mar 2024 • Shen Zheng, Anurag Ghosh, Srinivasa G. Narasimhan
Discovering that shifting the source scale distribution improves backbone features, we developed a instance-level warping guidance aimed at object region sampling to mitigate source scale bias in domain adaptation.
1 code implementation • 23 Aug 2023 • Nitin Nilesh, Tushar Sharma, Anurag Ghosh, C. V. Jawahar
In this work, we propose an end-to-end framework for player movement analysis for badminton matches on live broadcast match videos.