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of 218
pro vyhledávání: '"Patel, Priyanka P."'
Training methods to perform robust 3D human pose and shape (HPS) estimation requires diverse training images with accurate ground truth. While BEDLAM demonstrates the potential of traditional procedural graphics to generate such data, the training im
Externí odkaz:
http://arxiv.org/abs/2411.08663
Autor:
Patel, Priyanka, Black, Michael J.
We address the challenge of accurate 3D human pose and shape estimation from monocular images. The key to accuracy and robustness lies in high-quality training data. Existing training datasets containing real images with pseudo ground truth (pGT) use
Externí odkaz:
http://arxiv.org/abs/2411.08128
We address the problem of regressing 3D human pose and shape from a single image, with a focus on 3D accuracy. The current best methods leverage large datasets of 3D pseudo-ground-truth (p-GT) and 2D keypoints, leading to robust performance. With suc
Externí odkaz:
http://arxiv.org/abs/2404.16752
We introduce ChatPose, a framework employing Large Language Models (LLMs) to understand and reason about 3D human poses from images or textual descriptions. Our work is motivated by the human ability to intuitively understand postures from a single i
Externí odkaz:
http://arxiv.org/abs/2311.18836
Publikováno v:
CVPR 2023
We show, for the first time, that neural networks trained only on synthetic data achieve state-of-the-art accuracy on the problem of 3D human pose and shape (HPS) estimation from real images. Previous synthetic datasets have been small, unrealistic,
Externí odkaz:
http://arxiv.org/abs/2306.16940
Information technology and software services are pervasive, occupying the centre of most aspects of contemporary societies. This has given rise to commonly expected norms and expectations around how such systems should work, appropriate penalties for
Externí odkaz:
http://arxiv.org/abs/2201.02269
Autor:
Patel, Priyanka, Huang, Chun-Hao P., Tesch, Joachim, Hoffmann, David T., Tripathi, Shashank, Black, Michael J.
Publikováno v:
CVPR 2021
While the accuracy of 3D human pose estimation from images has steadily improved on benchmark datasets, the best methods still fail in many real-world scenarios. This suggests that there is a domain gap between current datasets and common scenes cont
Externí odkaz:
http://arxiv.org/abs/2104.14643
Autor:
Licorish, Sherlock A., Lee, Chan Won, Savarimuthu, Bastin Tony Roy, Patel, Priyanka, MacDonell, Stephen G.
Publikováno v:
Proceedings of the 21st Americas Conference on Information Systems (AMCIS2015). Puerto Rico, AISeL, 1-11. http://aisel.aisnet.org/amcis2015/VirtualComm/GeneralPresentations/7/
It is known that user involvement and user-centered design enhance system acceptance, particularly when end-users' views are considered early in the process. However, the increasingly common method of system deployment, through frequent releases via
Externí odkaz:
http://arxiv.org/abs/2103.00376
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