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pro vyhledávání: '"Farooq, Azib"'
Editing complex visual content based on ambiguous instructions remains a challenging problem in vision-language modeling. While existing models can contextualize content, they often struggle to grasp the underlying intent within a reference image or
Externí odkaz:
http://arxiv.org/abs/2412.10566
We introduce 3DEgo to address a novel problem of directly synthesizing photorealistic 3D scenes from monocular videos guided by textual prompts. Conventional methods construct a text-conditioned 3D scene through a three-stage process, involving pose
Externí odkaz:
http://arxiv.org/abs/2407.10102
The potential of deep learning, especially in medical imaging, initiated astonishing results and improved the methodologies after every passing day. Deep learning in radiology provides the opportunity to classify, detect and segment different disease
Externí odkaz:
http://arxiv.org/abs/2203.13461
Autor:
Bilal, Muhammad, Razzaq, Saqlain, Bhowmike, Nirman, Farooq, Azib, Zahid, Muhammad, Shoaib, Sultan
Publikováno v:
AI; Sep2024, Vol. 5 Issue 3, p1633-1647, 15p
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers