Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Ambrish Tyagi"'
Publikováno v:
3DV
Recovering 3D human pose from 2D joints is a highly unconstrained problem. We propose a novel neural network framework, PoseNet3D, that takes 2D joints as input and outputs 3D skeletons and SMPL body model parameters. By casting our learning approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d049ba054d1efda7cf9094995603e338
http://arxiv.org/abs/2003.03473
http://arxiv.org/abs/2003.03473
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110178
ECCV Workshops (4)
ECCV Workshops (4)
3D pose estimation from a single image is a challenging task in computer vision. We present a weakly supervised approach to estimate 3D pose points, given only 2D pose landmarks. Our method does not require correspondences between 2D and 3D points to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cba3cddb8493dd7550965e4d2fbd503
https://doi.org/10.1007/978-3-030-11018-5_7
https://doi.org/10.1007/978-3-030-11018-5_7
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110147
ECCV Workshops (3)
ECCV Workshops (3)
We propose a framework that harnesses visual cues in an unsupervised manner to learn the co-occurrence distribution of items in real-world images for complementary recommendation. Our model learns a non-linear transformation between the two manifolds
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::df4ac902b4fd6362333e633fee991abf
https://doi.org/10.1007/978-3-030-11015-4_7
https://doi.org/10.1007/978-3-030-11015-4_7
Autor:
Stefan Stojanov, Ambrish Tyagi, James M. Rehg, Ching-Hang Chen, Dylan Drover, Rohith Mv, Amit Agrawal
Publikováno v:
CVPR
We present an unsupervised learning approach to re- cover 3D human pose from 2D skeletal joints extracted from a single image. Our method does not require any multi- view image data, 3D skeletons, correspondences between 2D-3D points, or use previous
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80946e6a90c5b4caa9475899022d83bf
Autor:
Shashank Tripathi, Amit Agrawal, Siddhartha Chandra, James M. Rehg, Visesh Chari, Ambrish Tyagi
Publikováno v:
CVPR
We present a task-aware approach to synthetic data generation. Our framework employs a trainable synthesizer network that is optimized to produce meaningful training samples by assessing the strengths and weaknesses of a `target' network. The synthes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f018a39ed3c331a5cf0341ecd5dc9dd
Autor:
Jianping Shi, Ambrish Tyagi, Hang Zhang, Zhongyue Zhang, Xiaogang Wang, Amit Agrawal, Kristin J. Dana
Publikováno v:
CVPR
Recent work has made significant progress in improving spatial resolution for pixelwise labeling with Fully Convolutional Network (FCN) framework by employing Dilated/Atrous convolution, utilizing multi-scale features and refining boundaries. In this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2a190cca2d4a27b568dc9f2aa396f8f
Autor:
Vasileios Mylonakis, Rainer Stiefelhagen, Cedrick Rochet, Luca Cristoforetti, Gerasimos Potamianos, Ambrish Tyagi, Susanne Burger, Nicolas Moreau, Stephen M. Chu, Fotios Talantzis, Francesco Tobia, Keni Bernardin, Khalid Choukri, Jordi Turmo, Josep R. Casas, Aristodemos Pnevmatikakis, Djamel Mostefa
Publikováno v:
Language Resources and Evaluation. 41:389-407
The analysis of lectures and meetings inside smart rooms has recently attracted much interest in the literature, being the focus of international projects and technology evaluations. A key enabler for progress in this area is the availability of appr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::582bbe643881bd6e7fdb87156034fecc
https://doi.org/10.1007/s10579-007-9054-4
https://doi.org/10.1007/s10579-007-9054-4
Autor:
James W. Davis, Ambrish Tyagi
Publikováno v:
Image and Vision Computing. 24:455-472
We present a probabilistic reliable-inference framework to address the issue of rapid detection of human actions with low error rates. The approach determines the shortest video exposures needed for low-latency recognition by sequentially evaluating
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d17ac0123eec608657469da658773fe6
https://doi.org/10.1016/j.imavis.2006.01.012
https://doi.org/10.1016/j.imavis.2006.01.012
Autor:
Ambrish Tyagi, James W. Davis
Publikováno v:
CVPR
We present an online, recursive filtering technique to model linear dynamical systems that operate on the state space of symmetric positive definite matrices (tensors) that lie on a Riemannian manifold. The proposed approach describes a predict-and-u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c9f93237ba1f7f9adbdd669a4a2a608
https://doi.org/10.1109/cvpr.2008.4587519
https://doi.org/10.1109/cvpr.2008.4587519