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pro vyhledávání: '"Xie, Desai"'
Autor:
Xie, Desai, Xu, Zhan, Hong, Yicong, Tan, Hao, Liu, Difan, Liu, Feng, Kaufman, Arie, Zhou, Yang
Current frontier video diffusion models have demonstrated remarkable results at generating high-quality videos. However, they can only generate short video clips, normally around 10 seconds or 240 frames, due to computation limitations during trainin
Externí odkaz:
http://arxiv.org/abs/2410.08151
Autor:
Xie, Desai, Bi, Sai, Shu, Zhixin, Zhang, Kai, Xu, Zexiang, Zhou, Yi, Pirk, Sören, Kaufman, Arie, Sun, Xin, Tan, Hao
We present LRM-Zero, a Large Reconstruction Model (LRM) trained entirely on synthesized 3D data, achieving high-quality sparse-view 3D reconstruction. The core of LRM-Zero is our procedural 3D dataset, Zeroverse, which is automatically synthesized fr
Externí odkaz:
http://arxiv.org/abs/2406.09371
Autor:
Xie, Desai, Li, Jiahao, Tan, Hao, Sun, Xin, Shu, Zhixin, Zhou, Yi, Bi, Sai, Pirk, Sören, Kaufman, Arie E.
Multi-view diffusion models, obtained by applying Supervised Finetuning (SFT) to text-to-image diffusion models, have driven recent breakthroughs in text-to-3D research. However, due to the limited size and quality of existing 3D datasets, they still
Externí odkaz:
http://arxiv.org/abs/2312.13980