Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Agarwal, Aishwarya"'
We consider the problem of independently, in a disentangled fashion, controlling the outputs of text-to-image diffusion models with color and style attributes of a user-supplied reference image. We present the first training-free, test-time-only meth
Externí odkaz:
http://arxiv.org/abs/2409.02429
We consider the problem of customizing text-to-image diffusion models with user-supplied reference images. Given new prompts, the existing methods can capture the key concept from the reference images but fail to align the generated image with the pr
Externí odkaz:
http://arxiv.org/abs/2406.18893
Autor:
Rangwani, Harsh, Agarwal, Aishwarya, Kulkarni, Kuldeep, Babu, R. Venkatesh, Karanam, Srikrishna
Text-to-image generation from large generative models like Stable Diffusion, DALLE-2, etc., have become a common base for various tasks due to their superior quality and extensive knowledge bases. As image composition and generation are creative proc
Externí odkaz:
http://arxiv.org/abs/2406.10197
We consider the problem of constraining diffusion model outputs with a user-supplied reference image. Our key objective is to extract multiple attributes (e.g., color, object, layout, style) from this single reference image, and then generate new sam
Externí odkaz:
http://arxiv.org/abs/2311.11919
Autor:
Joseph, K J, Udhayanan, Prateksha, Shukla, Tripti, Agarwal, Aishwarya, Karanam, Srikrishna, Goswami, Koustava, Srinivasan, Balaji Vasan
Recent advances in text-guided image synthesis has dramatically changed how creative professionals generate artistic and aesthetically pleasing visual assets. To fully support such creative endeavors, the process should possess the ability to: 1) ite
Externí odkaz:
http://arxiv.org/abs/2309.00613
Recent works in self-supervised learning have shown impressive results on single-object images, but they struggle to perform well on complex multi-object images as evidenced by their poor visual grounding. To demonstrate this concretely, we propose v
Externí odkaz:
http://arxiv.org/abs/2306.14603
Autor:
Agarwal, Aishwarya, Karanam, Srikrishna, Joseph, K J, Saxena, Apoorv, Goswami, Koustava, Srinivasan, Balaji Vasan
While recent developments in text-to-image generative models have led to a suite of high-performing methods capable of producing creative imagery from free-form text, there are several limitations. By analyzing the cross-attention representations of
Externí odkaz:
http://arxiv.org/abs/2306.14544
We study a recently introduced class of strategic games that is motivated by and generalizes Schelling's well-known residential segregation model. These games are played on undirected graphs, with the set of agents partitioned into multiple types; ea
Externí odkaz:
http://arxiv.org/abs/1909.02421
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2021 Nov 01. 118(45), 1-10.
Externí odkaz:
https://www.jstor.org/stable/27093658
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.