Zobrazeno 1 - 10
of 7 860
pro vyhledávání: '"Patel, P. M."'
Autor:
Mohanta, Gurucharan, Patel, Ketan M.
A mechanism for the masses of third, second, and first generation charged fermions at the tree, 1-loop, and 2-loop levels, respectively, is proposed. The fermionic self-energy corrections that lead to this arrangement are induced through heavy vector
Externí odkaz:
http://arxiv.org/abs/2406.19179
Text-based 2D diffusion models have demonstrated impressive capabilities in image generation and editing. Meanwhile, the 2D diffusion models also exhibit substantial potentials for 3D editing tasks. However, how to achieve consistent edits across mul
Externí odkaz:
http://arxiv.org/abs/2406.17396
Autor:
Zhang, Ke, Patel, Vishal M.
Pixel-level dense labeling is both resource-intensive and time-consuming, whereas weak labels such as scribble present a more feasible alternative to full annotations. However, training segmentation networks with weak supervision from scribbles remai
Externí odkaz:
http://arxiv.org/abs/2406.13237
Photographs captured in unstructured tourist environments frequently exhibit variable appearances and transient occlusions, challenging accurate scene reconstruction and inducing artifacts in novel view synthesis. Although prior approaches have integ
Externí odkaz:
http://arxiv.org/abs/2406.10373
Diffusion models have emerged as a formidable tool for training-free conditional generation.However, a key hurdle in inference-time guidance techniques is the need for compute-heavy backpropagation through the diffusion network for estimating the gui
Externí odkaz:
http://arxiv.org/abs/2406.02549
Autor:
Lo, Shao-Yuan, Patel, Vishal M.
Deep networks are vulnerable to adversarial examples. Adversarial Training (AT) has been a standard foundation of modern adversarial defense approaches due to its remarkable effectiveness. However, AT is extremely time-consuming, refraining it from w
Externí odkaz:
http://arxiv.org/abs/2405.11708
In recent years, various large foundation models have been proposed for image segmentation. There models are often trained on large amounts of data corresponding to general computer vision tasks. Hence, these models do not perform well on medical dat
Externí odkaz:
http://arxiv.org/abs/2405.10913
Autor:
Narayan, Kartik, Patel, Vishal M.
Face recognition technology has become an integral part of modern security systems and user authentication processes. However, these systems are vulnerable to spoofing attacks and can easily be circumvented. Most prior research in face anti-spoofing
Externí odkaz:
http://arxiv.org/abs/2404.14406
One of the challenges for neural networks in real-life applications is the overconfident errors these models make when the data is not from the original training distribution. Addressing this issue is known as Out-of-Distribution (OOD) detection. Man
Externí odkaz:
http://arxiv.org/abs/2404.12368
LiDAR datasets for autonomous driving exhibit biases in properties such as point cloud density, range, and object dimensions. As a result, object detection networks trained and evaluated in different environments often experience performance degradat
Externí odkaz:
http://arxiv.org/abs/2404.11764