Zobrazeno 1 - 10
of 400
pro vyhledávání: '"Bhattacharyya, Shuvra"'
Autor:
Yim, Jinsub, Lee, Hyungtae, Eum, Sungmin, Shen, Yi-Ting, Zhang, Yan, Kwon, Heesung, Bhattacharyya, Shuvra S.
We introduce Synthetic Playground (SynPlay), a new synthetic human dataset that aims to bring out the diversity of human appearance in the real world. We focus on two factors to achieve a level of diversity that has not yet been seen in previous work
Externí odkaz:
http://arxiv.org/abs/2408.11814
We present a framework for diversifying human poses in a synthetic dataset for aerial-view human detection. Our method firstly constructs a set of novel poses using a pose generator and then alters images in the existing synthetic dataset to assume t
Externí odkaz:
http://arxiv.org/abs/2405.15939
Aerial-view human detection has a large demand for large-scale data to capture more diverse human appearances compared to ground-view human detection. Therefore, synthetic data can be a good resource to expand data, but the domain gap with real-world
Externí odkaz:
http://arxiv.org/abs/2405.15203
Biometric applications, such as person re-identification (ReID), are often deployed on energy constrained devices. While recent ReID methods prioritize high retrieval performance, they often come with large computational costs and high search time, r
Externí odkaz:
http://arxiv.org/abs/2308.11900
To effectively interrogate UAV-based images for detecting objects of interest, such as humans, it is essential to acquire large-scale UAV-based datasets that include human instances with various poses captured from widely varying viewing angles. As a
Externí odkaz:
http://arxiv.org/abs/2211.01778
Autor:
Shen, Yi-Ting, Lee, Yaesop, Kwon, Heesung, Conover, Damon M., Bhattacharyya, Shuvra S., Vale, Nikolas, Gray, Joshua D., Leong, G. Jeremy, Evensen, Kenneth, Skirlo, Frank
Publikováno v:
IEEE Access, vol. 11, pp. 80958-80972, 2023
Learning to detect objects, such as humans, in imagery captured by an unmanned aerial vehicle (UAV) usually suffers from tremendous variations caused by the UAV's position towards the objects. In addition, existing UAV-based benchmark datasets do not
Externí odkaz:
http://arxiv.org/abs/2209.00128
Autor:
Xie, Jing, Yan, Yuzhong, Saxena, Abhishek, Qiu, Qiang, Chen, Jiangong, Sun, Hongyu, Chen, Rong, Bhattacharyya, Shuvra S.
Publikováno v:
In Neurocomputing 1 January 2025 611
