Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Tadevosyan, Vahram"'
Autor:
Henschel, Roberto, Khachatryan, Levon, Hayrapetyan, Daniil, Poghosyan, Hayk, Tadevosyan, Vahram, Wang, Zhangyang, Navasardyan, Shant, Shi, Humphrey
Text-to-video diffusion models enable the generation of high-quality videos that follow text instructions, making it easy to create diverse and individual content. However, existing approaches mostly focus on high-quality short video generation (typi
Externí odkaz:
http://arxiv.org/abs/2403.14773
Autor:
Khachatryan, Levon, Movsisyan, Andranik, Tadevosyan, Vahram, Henschel, Roberto, Wang, Zhangyang, Navasardyan, Shant, Shi, Humphrey
Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without any traini
Externí odkaz:
http://arxiv.org/abs/2303.13439
Autor:
Xu, Xingqian, Navasardyan, Shant, Tadevosyan, Vahram, Sargsyan, Andranik, Mu, Yadong, Shi, Humphrey
Image completion with large-scale free-form missing regions is one of the most challenging tasks for the computer vision community. While researchers pursue better solutions, drawbacks such as pattern unawareness, blurry textures, and structure disto
Externí odkaz:
http://arxiv.org/abs/2211.03700