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pro vyhledávání: '"Stan, Gabriela Ben Melech"'
Autor:
Cai, Zhipeng, Mueller, Matthias, Birkl, Reiner, Wofk, Diana, Tseng, Shao-Yen, Cheng, JunDa, Stan, Gabriela Ben-Melech, Lal, Vasudev, Paulitsch, Michael
In the current era of generative AI breakthroughs, generating panoramic scenes from a single input image remains a key challenge. Most existing methods use diffusion-based iterative or simultaneous multi-view inpainting. However, the lack of global s
Externí odkaz:
http://arxiv.org/abs/2406.01843
Autor:
Stan, Gabriela Ben Melech, Aflalo, Estelle, Rohekar, Raanan Yehezkel, Bhiwandiwalla, Anahita, Tseng, Shao-Yen, Olson, Matthew Lyle, Gurwicz, Yaniv, Wu, Chenfei, Duan, Nan, Lal, Vasudev
In the rapidly evolving landscape of artificial intelligence, multi-modal large language models are emerging as a significant area of interest. These models, which combine various forms of data input, are becoming increasingly popular. However, under
Externí odkaz:
http://arxiv.org/abs/2404.03118
Autor:
Chatterjee, Agneet, Stan, Gabriela Ben Melech, Aflalo, Estelle, Paul, Sayak, Ghosh, Dhruba, Gokhale, Tejas, Schmidt, Ludwig, Hajishirzi, Hannaneh, Lal, Vasudev, Baral, Chitta, Yang, Yezhou
One of the key shortcomings in current text-to-image (T2I) models is their inability to consistently generate images which faithfully follow the spatial relationships specified in the text prompt. In this paper, we offer a comprehensive investigation
Externí odkaz:
http://arxiv.org/abs/2404.01197
Autor:
Stan, Gabriela Ben Melech, Wofk, Diana, Aflalo, Estelle, Tseng, Shao-Yen, Cai, Zhipeng, Paulitsch, Michael, Lal, Vasudev
Latent diffusion models have proven to be state-of-the-art in the creation and manipulation of visual outputs. However, as far as we know, the generation of depth maps jointly with RGB is still limited. We introduce LDM3D-VR, a suite of diffusion mod
Externí odkaz:
http://arxiv.org/abs/2311.03226
Autor:
Stan, Gabriela Ben Melech, Wofk, Diana, Fox, Scottie, Redden, Alex, Saxton, Will, Yu, Jean, Aflalo, Estelle, Tseng, Shao-Yen, Nonato, Fabio, Muller, Matthias, Lal, Vasudev
This research paper proposes a Latent Diffusion Model for 3D (LDM3D) that generates both image and depth map data from a given text prompt, allowing users to generate RGBD images from text prompts. The LDM3D model is fine-tuned on a dataset of tuples
Externí odkaz:
http://arxiv.org/abs/2305.10853
Autor:
Madasu, Avinash, Aflalo, Estelle, Stan, Gabriela Ben Melech, Rosenman, Shachar, Tseng, Shao-Yen, Bertasius, Gedas, Lal, Vasudev
Multi-modal retrieval has seen tremendous progress with the development of vision-language models. However, further improving these models require additional labelled data which is a huge manual effort. In this paper, we propose a framework MuMUR, th
Externí odkaz:
http://arxiv.org/abs/2208.11553
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Autor:
Stan, Gabriela Ben‐Melech1,2 (AUTHOR), Dhaka, Kapil1 (AUTHOR), Toroker, Maytal Caspary1,2 (AUTHOR) maytalc@tx.technion.ac.il
Publikováno v:
Israel Journal of Chemistry. Aug2020, Vol. 60 Issue 8/9, p888-896. 9p.
Akademický článek
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