Zobrazeno 1 - 10
of 82
pro vyhledávání: '"BHATTACHARYA, UJJWAL"'
Autor:
Hazra, Saheli, Das, Sudip, Choudhary, Rohit, Das, Arindam, Sistu, Ganesh, Eising, Ciaran, Bhattacharya, Ujjwal
Applying pseudo labeling techniques has been found to be advantageous in semi-supervised 3D object detection (SSOD) in Bird's-Eye-View (BEV) for autonomous driving, particularly where labeled data is limited. In the literature, Exponential Moving Ave
Externí odkaz:
http://arxiv.org/abs/2412.04337
Autor:
Das, Arindam, Paul, Sudarshan, Scholz, Niko, Malviya, Akhilesh Kumar, Sistu, Ganesh, Bhattacharya, Ujjwal, Eising, Ciarán
Accurate obstacle identification represents a fundamental challenge within the scope of near-field perception for autonomous driving. Conventionally, fisheye cameras are frequently employed for comprehensive surround-view perception, including rear-v
Externí odkaz:
http://arxiv.org/abs/2402.00637
Autor:
Das, Arindam, Das, Sudip, Sistu, Ganesh, Horgan, Jonathan, Bhattacharya, Ujjwal, Jones, Edward, Glavin, Martin, Eising, Ciarán
Publikováno v:
In proceedings of the IEEE 2023 International Conference on Image Processing
Multimodal learning, particularly for pedestrian detection, has recently received emphasis due to its capability to function equally well in several critical autonomous driving scenarios such as low-light, night-time, and adverse weather conditions.
Externí odkaz:
http://arxiv.org/abs/2302.12589
Autor:
Das, Arindam, Das, Sudip, Sistu, Ganesh, Horgan, Jonathan, Bhattacharya, Ujjwal, Jones, Edward, Glavin, Martin, Eising, Ciarán
Publikováno v:
Proceedings of the 2022 Irish Machine Vision and Image Processing Conference
Most of the existing works on pedestrian pose estimation do not consider estimating the pose of an occluded pedestrian, as the annotations of the occluded parts are not available in relevant automotive datasets. For example, CityPersons, a well-known
Externí odkaz:
http://arxiv.org/abs/2206.07510
Autor:
Dasgupta, Subhrajyoti, Das, Arindam, Yogamani, Senthil, Das, Sudip, Eising, Ciaran, Bursuc, Andrei, Bhattacharya, Ujjwal
Shadows are frequently encountered natural phenomena that significantly hinder the performance of computer vision perception systems in practical settings, e.g., autonomous driving. A solution to this would be to eliminate shadow regions from the ima
Externí odkaz:
http://arxiv.org/abs/2203.15441
Pedestrian Detection is the most critical module of an Autonomous Driving system. Although a camera is commonly used for this purpose, its quality degrades severely in low-light night time driving scenarios. On the other hand, the quality of a therma
Externí odkaz:
http://arxiv.org/abs/2105.12713
Amidst an increasing number of infected cases during the Covid-19 pandemic, it is essential to trace, as early as possible, the susceptible people who might have been infected by the disease due to their close proximity with people who were tested po
Externí odkaz:
http://arxiv.org/abs/2004.08851
Pose estimation in the wild is a challenging problem, particularly in situations of (i) occlusions of varying degrees and (ii) crowded outdoor scenes. Most of the existing studies of pose estimation did not report the performance in similar situation
Externí odkaz:
http://arxiv.org/abs/2002.06429
Automatic detection of scene texts in the wild is a challenging problem, particularly due to the difficulties in handling (i) occlusions of varying percentages, (ii) widely different scales and orientations, (iii) severe degradations in the image qua
Externí odkaz:
http://arxiv.org/abs/2002.06423
Studies of object detection and localization, particularly pedestrian detection have received considerable attention in recent times due to its several prospective applications such as surveillance, driving assistance, autonomous cars, etc. Also, a s
Externí odkaz:
http://arxiv.org/abs/1912.10241