Zobrazeno 1 - 10
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pro vyhledávání: '"P Samaras"'
Diffusion models have dominated the field of large, generative image models, with the prime examples of Stable Diffusion and DALL-E 3 being widely adopted. These models have been trained to perform text-conditioned generation on vast numbers of image
Externí odkaz:
http://arxiv.org/abs/2410.18804
Diffusion models excel at creating visually impressive images but often struggle to generate images with a specified topology. The Betti number, which represents the number of structures in an image, is a fundamental measure in topology. Yet, diffusi
Externí odkaz:
http://arxiv.org/abs/2410.16646
Autor:
Banik, Indranil, Samaras, Nick
We consider constraints on the Hubble parameter $H_0$ and the matter density parameter $\Omega_{\mathrm{M}}$ from: (i) the age of the Universe based on old stars and stellar populations in the Galactic disc and halo (Cimatti & Moresco 2023); (ii) the
Externí odkaz:
http://arxiv.org/abs/2410.00804
Human emotional expression is inherently dynamic, complex, and fluid, characterized by smooth transitions in intensity throughout verbal communication. However, the modeling of such intensity fluctuations has been largely overlooked by previous audio
Externí odkaz:
http://arxiv.org/abs/2409.19501
Autor:
Chatziagapi, Aggelina, Chaudhuri, Bindita, Kumar, Amit, Ranjan, Rakesh, Samaras, Dimitris, Sarafianos, Nikolaos
We introduce a novel framework that learns a dynamic neural radiance field (NeRF) for full-body talking humans from monocular videos. Prior work represents only the body pose or the face. However, humans communicate with their full body, combining bo
Externí odkaz:
http://arxiv.org/abs/2409.16666
We introduce a novel method for joint expression and audio-guided talking face generation. Recent approaches either struggle to preserve the speaker identity or fail to produce faithful facial expressions. To address these challenges, we propose a Ne
Externí odkaz:
http://arxiv.org/abs/2409.12156
Shadow boundaries can be confused with material boundaries as both exhibit sharp changes in luminance or contrast within a scene. However, shadows do not modify the intrinsic color or texture of surfaces. Therefore, on both sides of shadow edges trav
Externí odkaz:
http://arxiv.org/abs/2409.06848
Autor:
Mondal, Sounak, Ahn, Seoyoung, Yang, Zhibo, Balasubramanian, Niranjan, Samaras, Dimitris, Zelinsky, Gregory, Hoai, Minh
For computer systems to effectively interact with humans using spoken language, they need to understand how the words being generated affect the users' moment-by-moment attention. Our study focuses on the incremental prediction of attention as a pers
Externí odkaz:
http://arxiv.org/abs/2407.19605
Advances in generative models increase the need for sample quality assessment. To do so, previous methods rely on a pre-trained feature extractor to embed the generated samples and real samples into a common space for comparison. However, different f
Externí odkaz:
http://arxiv.org/abs/2407.15171
Autor:
Le, Minh-Quan, Graikos, Alexandros, Yellapragada, Srikar, Gupta, Rajarsi, Saltz, Joel, Samaras, Dimitris
Synthesizing high-resolution images from intricate, domain-specific information remains a significant challenge in generative modeling, particularly for applications in large-image domains such as digital histopathology and remote sensing. Existing m
Externí odkaz:
http://arxiv.org/abs/2407.14709