Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Singhal, Prateek"'
Autor:
Feng, Jianwei, Singhal, Prateek
Publikováno v:
WACV 2024
Style transfer for human face has been widely researched in recent years. Majority of the existing approaches work in 2D image domain and have 3D inconsistency issue when applied on different viewpoints of the same face. In this paper, we tackle the
Externí odkaz:
http://arxiv.org/abs/2311.13168
Large-scale pretraining and instruction tuning have been successful for training general-purpose language models with broad competencies. However, extending to general-purpose vision-language models is challenging due to the distributional diversity
Externí odkaz:
http://arxiv.org/abs/2311.07449
Empirical studies suggest that machine learning models trained with empirical risk minimization (ERM) often rely on attributes that may be spuriously correlated with the class labels. Such models typically lead to poor performance during inference fo
Externí odkaz:
http://arxiv.org/abs/2212.01433
Autor:
Singhal, Prateek
An on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry is presented. Using a combination of vision and
Externí odkaz:
http://hdl.handle.net/1853/54970
Autor:
Srivastava, Prabhat Kr., Pandey, Ram Kinkar, Srivastava, Gaurav Kumar, Anand, Nishant, Krishna, Kunchanapalli Rama, Singhal, Prateek, Sharma, Aditi
Publikováno v:
Journal of Intelligent Systems & Internet of Things; 2024, Vol. 13 Issue 2, p60-77, 18p
We present an on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry. Using a combination of vision and od
Externí odkaz:
http://arxiv.org/abs/1603.04117
Image based reconstruction of urban environments is a challenging problem that deals with optimization of large number of variables, and has several sources of errors like the presence of dynamic objects. Since most large scale approaches make the as
Externí odkaz:
http://arxiv.org/abs/1504.07269
While the literature has been fairly dense in the areas of scene understanding and semantic labeling there have been few works that make use of motion cues to embellish semantic performance and vice versa. In this paper, we address the problem of sem
Externí odkaz:
http://arxiv.org/abs/1504.06587
Detecting multiple planes in images is a challenging problem, but one with many applications. Recent work such as J-Linkage and Ordered Residual Kernels have focussed on developing a domain independent approach to detect multiple structures. These mu
Externí odkaz:
http://arxiv.org/abs/1312.6506