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pro vyhledávání: '"Huo, Jingyang"'
Recent fMRI-to-image approaches mainly focused on associating fMRI signals with specific conditions of pre-trained diffusion models. These approaches, while producing high-quality images, capture only a limited aspect of the complex information in fM
Externí odkaz:
http://arxiv.org/abs/2403.18211
With the rise of short video platforms represented by TikTok, the trend of users expressing their creativity through photos and videos has increased dramatically. However, ordinary users lack the professional skills to produce high-quality videos usi
Externí odkaz:
http://arxiv.org/abs/2402.15746
The exploration of brain activity and its decoding from fMRI data has been a longstanding pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics, and virtual reality. Previous approaches have primarily focused
Externí odkaz:
http://arxiv.org/abs/2311.00342
We present a significant breakthrough in 3D shape generation by scaling it to unprecedented dimensions. Through the adaptation of the Auto-Regressive model and the utilization of large language models, we have developed a remarkable model with an ast
Externí odkaz:
http://arxiv.org/abs/2306.11510
Most existing works solving Room-to-Room VLN problem only utilize RGB images and do not consider local context around candidate views, which lack sufficient visual cues about surrounding environment. Moreover, natural language contains complex semant
Externí odkaz:
http://arxiv.org/abs/2305.17102
Akademický článek
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Akademický článek
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We present a significant breakthrough in 3D shape generation by scaling it to unprecedented dimensions. Through the adaptation of the Auto-Regressive model and the utilization of large language models, we have developed a remarkable model with an ast
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32f79b202466cfa7123aef96126e879e
http://arxiv.org/abs/2306.11510
http://arxiv.org/abs/2306.11510