Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Prathosh A P"'
Autor:
Goswami, Ashish, Modi, Satyam Kumar, Deshineni, Santhosh Rishi, Singh, Harman, P, Prathosh A., Singla, Parag
Text-to-image (T2I) generation has seen significant progress with diffusion models, enabling generation of photo-realistic images from text prompts. Despite this progress, existing methods still face challenges in following complex text prompts, espe
Externí odkaz:
http://arxiv.org/abs/2412.06089
Autor:
Tyagi, Aayush Kumar, Mishra, Vaibhav, Tiwari, Ashok, Mehra, Lalita, Das, Prasenjit, Makharia, Govind, AP, Prathosh, Mausam
Celiac disease is an autoimmune disorder triggered by the consumption of gluten. It causes damage to the villi, the finger-like projections in the small intestine that are responsible for nutrient absorption. Additionally, the crypts, which form the
Externí odkaz:
http://arxiv.org/abs/2412.01182
With the rise of marine exploration, underwater imaging has gained significant attention as a research topic. Underwater video enhancement has become crucial for real-time computer vision tasks in marine exploration. However, most existing methods fo
Externí odkaz:
http://arxiv.org/abs/2411.05886
We introduce $\texttt{ReMOVE}$, a novel reference-free metric for assessing object erasure efficacy in diffusion-based image editing models post-generation. Unlike existing measures such as LPIPS and CLIPScore, $\texttt{ReMOVE}$ addresses the challen
Externí odkaz:
http://arxiv.org/abs/2409.00707
Given unstructured text, Large Language Models (LLMs) are adept at answering simple (single-hop) questions. However, as the complexity of the questions increase, the performance of LLMs degrade. We believe this is due to the overhead associated with
Externí odkaz:
http://arxiv.org/abs/2406.06027
Neural operators extend data-driven models to map between infinite-dimensional functional spaces. While these operators perform effectively in either the time or frequency domain, their performance may be limited when applied to non-stationary spatia
Externí odkaz:
http://arxiv.org/abs/2406.02597
Knowledge distillation, a widely used model compression technique, works on the basis of transferring knowledge from a cumbersome teacher model to a lightweight student model. The technique involves jointly optimizing the task specific and knowledge
Externí odkaz:
http://arxiv.org/abs/2405.08019
Cancer, a leading cause of death globally, occurs due to genomic changes and manifests heterogeneously across patients. To advance research on personalized treatment strategies, the effectiveness of various drugs on cells derived from cancers (`cell
Externí odkaz:
http://arxiv.org/abs/2405.04078
In order to adhere to regulatory standards governing individual data privacy and safety, machine learning models must systematically eliminate information derived from specific subsets of a user's training data that can no longer be utilized. The eme
Externí odkaz:
http://arxiv.org/abs/2403.16246
Autor:
Kumar, Aman, Anand, Khushboo, Mandloi, Shubham, Mishra, Ashutosh, Thakur, Avinash, Kasera, Neeraj, P, Prathosh A
Generative Adversarial Networks (GANs) have proven to exhibit remarkable performance and are widely used across many generative computer vision applications. However, the unprecedented demand for the deployment of GANs on resource-constrained edge de
Externí odkaz:
http://arxiv.org/abs/2403.08261