Zobrazeno 1 - 10
of 213
pro vyhledávání: '"Bao FAN"'
Publikováno v:
Chengshi guidao jiaotong yanjiu, Vol 27, Iss 1, Pp 265-268,275 (2024)
[Objective] To analyze the allowable charge quantity of flammable refrigerants in RTVAC (rail transit vehicle air-conditioners), it is necessary to explore the feasibility and solutions for the safe application of environmentally friendly flammable r
Externí odkaz:
https://doaj.org/article/395e088ccb584bbf8ef7a2457e9dbc89
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
Ovarian cancer is the most fatal of all female reproductive cancers. The fatality rate of OC is the highest among gynecological malignant tumors, and cytoreductive surgery is a common surgical procedure for patients with advanced ovarian cancer. To a
Externí odkaz:
https://doaj.org/article/4f5dbd204ff44cdf9031669e3c2a2031
Diffusion models (DMs) have become the dominant paradigm of generative modeling in a variety of domains by learning stochastic processes from noise to data. Recently, diffusion denoising bridge models (DDBMs), a new formulation of generative modeling
Externí odkaz:
http://arxiv.org/abs/2410.22637
Denoising diffusion bridge models (DDBMs) are a powerful variant of diffusion models for interpolating between two arbitrary paired distributions given as endpoints. Despite their promising performance in tasks like image translation, DDBMs require a
Externí odkaz:
http://arxiv.org/abs/2405.15885
Autor:
Bao, Fan, Xiang, Chendong, Yue, Gang, He, Guande, Zhu, Hongzhou, Zheng, Kaiwen, Zhao, Min, Liu, Shilong, Wang, Yaole, Zhu, Jun
We introduce Vidu, a high-performance text-to-video generator that is capable of producing 1080p videos up to 16 seconds in a single generation. Vidu is a diffusion model with U-ViT as its backbone, which unlocks the scalability and the capability fo
Externí odkaz:
http://arxiv.org/abs/2405.04233
Recently, diffusion models have achieved great success in generative tasks. Sampling from diffusion models is equivalent to solving the reverse diffusion stochastic differential equations (SDEs) or the corresponding probability flow ordinary differen
Externí odkaz:
http://arxiv.org/abs/2311.00941
In this paper, we present ControlVideo, a novel method for text-driven video editing. Leveraging the capabilities of text-to-image diffusion models and ControlNet, ControlVideo aims to enhance the fidelity and temporal consistency of videos that alig
Externí odkaz:
http://arxiv.org/abs/2305.17098
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation
Score distillation sampling (SDS) has shown great promise in text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models, but suffers from over-saturation, over-smoothing, and low-diversity problems. In this work, we pro
Externí odkaz:
http://arxiv.org/abs/2305.16213
Large-scale diffusion models like Stable Diffusion are powerful and find various real-world applications while customizing such models by fine-tuning is both memory and time inefficient. Motivated by the recent progress in natural language processing
Externí odkaz:
http://arxiv.org/abs/2303.18181
Autor:
Bao, Fan, Nie, Shen, Xue, Kaiwen, Li, Chongxuan, Pu, Shi, Wang, Yaole, Yue, Gang, Cao, Yue, Su, Hang, Zhu, Jun
This paper proposes a unified diffusion framework (dubbed UniDiffuser) to fit all distributions relevant to a set of multi-modal data in one model. Our key insight is -- learning diffusion models for marginal, conditional, and joint distributions can
Externí odkaz:
http://arxiv.org/abs/2303.06555