Zobrazeno 1 - 10
of 292
pro vyhledávání: '"Chen, Kefan"'
The growing interest in fair AI development is evident. The ''Leave No One Behind'' initiative urges us to address multiple and intersecting forms of inequality in accessing services, resources, and opportunities, emphasising the significance of fair
Externí odkaz:
http://arxiv.org/abs/2407.03133
Autor:
Pokhariya, Chandradeep, Shah, Ishaan N, Xing, Angela, Li, Zekun, Chen, Kefan, Sharma, Avinash, Sridhar, Srinath
Understanding how we grasp objects with our hands has important applications in areas like robotics and mixed reality. However, this challenging problem requires accurate modeling of the contact between hands and objects. To capture grasps, existing
Externí odkaz:
http://arxiv.org/abs/2312.02137
Autor:
Lu, Cheng-You, Zhou, Peisen, Xing, Angela, Pokhariya, Chandradeep, Dey, Arnab, Shah, Ishaan, Mavidipalli, Rugved, Hu, Dylan, Comport, Andrew, Chen, Kefan, Sridhar, Srinath
Advances in neural fields are enabling high-fidelity capture of the shape and appearance of dynamic 3D scenes. However, their capabilities lag behind those offered by conventional representations such as 2D videos because of algorithmic challenges an
Externí odkaz:
http://arxiv.org/abs/2307.16897
Measuring the distance between machine-produced and human language is a critical open problem. Inspired by empirical findings from psycholinguistics on the periodicity of entropy in language, we propose FACE, a set of metrics based on Fourier Analysi
Externí odkaz:
http://arxiv.org/abs/2305.10307
Socially Assistive Robots (SARs) have shown promising potential in therapeutic scenarios as decision-making instructors or motivational companions. In human-human therapy, experts often communicate the thought process behind the decisions they make t
Externí odkaz:
http://arxiv.org/abs/2303.14054
Autor:
Fu, Yong, Qiao, HongXia, Feng, Qiong, Chen, KeFan, Li, YanQi, Jia, Zhenyu, Xue, CuiZhen, Hakuzweyezu, Theogene
Publikováno v:
In Materials Today Communications August 2024 40
Publikováno v:
In Journal of Building Engineering 1 November 2024 96
Publikováno v:
In Solar Energy October 2024 281
Publikováno v:
In Journal of Building Engineering 1 October 2024 94
Modern deep learning techniques that regress the relative camera pose between two images have difficulty dealing with challenging scenarios, such as large camera motions resulting in occlusions and significant changes in perspective that leave little
Externí odkaz:
http://arxiv.org/abs/2106.03336