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pro vyhledávání: '"Tiwari, Lokender"'
Autor:
Chanda, Sushovan, Tiwari, Amogh, Tiwari, Lokender, Bhowmick, Brojeshwar, Sharma, Avinash, Barua, Hrishav
Recovering temporally consistent 3D human body pose, shape and motion from a monocular video is a challenging task due to (self-)occlusions, poor lighting conditions, complex articulated body poses, depth ambiguity, and limited availability of annota
Externí odkaz:
http://arxiv.org/abs/2311.11662
Deep Neural Networks (DNNs) are often criticized for being susceptible to adversarial attacks. Most successful defense strategies adopt adversarial training or random input transformations that typically require retraining or fine-tuning the model to
Externí odkaz:
http://arxiv.org/abs/2006.10679
Autor:
Tiwari, Lokender, Anand, Saket
Robust multiple model fitting plays a crucial role in many computer vision applications. Unlike single model fitting problems, the multi-model fitting has additional challenges. The unknown number of models and the inlier noise scale are the two most
Externí odkaz:
http://arxiv.org/abs/2006.02413
Autor:
Tiwari, Lokender, Ji, Pan, Tran, Quoc-Huy, Zhuang, Bingbing, Anand, Saket, Chandraker, Manmohan
Classical monocular Simultaneous Localization And Mapping (SLAM) and the recently emerging convolutional neural networks (CNNs) for monocular depth prediction represent two largely disjoint approaches towards building a 3D map of the surrounding envi
Externí odkaz:
http://arxiv.org/abs/2004.10681
Autor:
Gadipudi, Nivesh, Elamvazuthi, Irraivan, Izhar, Lila Iznita, Tiwari, Lokender, Hebbalaguppe, Ramya, Lu, Cheng-Kai, Doss, Arockia Selvakumar Arockia
Publikováno v:
Visual Computer; Nov2023, Vol. 39 Issue 11, p5897-5924, 28p
Akademický článek
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Autor:
Tiwari, Lokender, Anand, Saket
Publikováno v:
2016 IEEE International Conference on Image Processing (ICIP); 2016, p3728-3732, 5p
Publikováno v:
2014 International Conference on Information Technology; 2014, p100-105, 6p