Zobrazeno 1 - 10
of 1 862
pro vyhledávání: '"Motion-consistency"'
Autor:
Wang, Chenyu, Yan, Shuo, Chen, Yixuan, Wang, Yujiang, Dong, Mingzhi, Yang, Xiaochen, Li, Dongsheng, Dick, Robert P., Lv, Qin, Yang, Fan, Lu, Tun, Gu, Ning, Shang, Li
Video generation using diffusion-based models is constrained by high computational costs due to the frame-wise iterative diffusion process. This work presents a Diffusion Reuse MOtion (Dr. Mo) network to accelerate latent video generation. Our key di
Externí odkaz:
http://arxiv.org/abs/2409.12532
Diffusion models usher a new era of video editing, flexibly manipulating the video contents with text prompts. Despite the widespread application demand in editing human-centered videos, these models face significant challenges in handling complex ob
Externí odkaz:
http://arxiv.org/abs/2408.07481
Significant advancements have been made in video generative models recently. Unlike image generation, video generation presents greater challenges, requiring not only generating high-quality frames but also ensuring temporal consistency across these
Externí odkaz:
http://arxiv.org/abs/2407.16124
Autor:
Zhai, Yuanhao, Lin, Kevin, Yang, Zhengyuan, Li, Linjie, Wang, Jianfeng, Lin, Chung-Ching, Doermann, David, Yuan, Junsong, Wang, Lijuan
Image diffusion distillation achieves high-fidelity generation with very few sampling steps. However, applying these techniques directly to video diffusion often results in unsatisfactory frame quality due to the limited visual quality in public vide
Externí odkaz:
http://arxiv.org/abs/2406.06890
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 5569-5583 (2024)
Abstract Robust matching, especially the number, precision and distribution of feature point matching, directly affects the effect of 3D reconstruction. However, the existing methods rarely consider these three aspects comprehensively to improve the
Externí odkaz:
https://doaj.org/article/7a96d884b65444e9b004f87bd057df13
Deep learning algorithms have driven expressive progress in many complex tasks. The loss function is a core component of deep learning techniques, guiding the learning process of neural networks. This paper contributes by introducing a consistency lo
Externí odkaz:
http://arxiv.org/abs/2401.10857
Publikováno v:
In ISPRS Journal of Photogrammetry and Remote Sensing December 2024 218 Part A:368-388
Akademický článek
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Akademický článek
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Autor:
Shen, Dong1 (AUTHOR), Fang, Haoyu1 (AUTHOR) 1197658404@qq.com, Li, Qiang1 (AUTHOR), Liu, Jiale1 (AUTHOR), Guo, Sheng1 (AUTHOR)
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 2023, Vol. 44 Issue 5, p7501-7512. 12p.