Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Feng, Mengyang"'
Recent advancements in human video synthesis have enabled the generation of high-quality videos through the application of stable diffusion models. However, existing methods predominantly concentrate on animating solely the human element (the foregro
Externí odkaz:
http://arxiv.org/abs/2405.16393
Text-guided domain adaptation and generation of 3D-aware portraits find many applications in various fields. However, due to the lack of training data and the challenges in handling the high variety of geometry and appearance, the existing methods fo
Externí odkaz:
http://arxiv.org/abs/2312.16837
Autor:
Feng, Mengyang, Liu, Jinlin, Yu, Kai, Yao, Yuan, Hui, Zheng, Guo, Xiefan, Lin, Xianhui, Xue, Haolan, Shi, Chen, Li, Xiaowen, Li, Aojie, Kang, Xiaoyang, Lei, Biwen, Cui, Miaomiao, Ren, Peiran, Xie, Xuansong
In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of the target
Externí odkaz:
http://arxiv.org/abs/2312.05107
We present Boosting3D, a multi-stage single image-to-3D generation method that can robustly generate reasonable 3D objects in different data domains. The point of this work is to solve the view consistency problem in single image-guided 3D generation
Externí odkaz:
http://arxiv.org/abs/2311.13617
This is a technical report on the 360-degree panoramic image generation task based on diffusion models. Unlike ordinary 2D images, 360-degree panoramic images capture the entire $360^\circ\times 180^\circ$ field of view. So the rightmost and the left
Externí odkaz:
http://arxiv.org/abs/2311.13141
Limited by the nature of the low-dimensional representational capacity of 3DMM, most of the 3DMM-based face reconstruction (FR) methods fail to recover high-frequency facial details, such as wrinkles, dimples, etc. Some attempt to solve the problem b
Externí odkaz:
http://arxiv.org/abs/2302.14434
Publikováno v:
In Journal of Crystal Growth 1 February 2023 603
Publikováno v:
In Micro and Nanostructures September 2022 169
We propose a novel unsupervised game-theoretic salient object detection algorithm that does not require labeled training data. First, saliency detection problem is formulated as a non-cooperative game, hereinafter referred to as Saliency Game, in whi
Externí odkaz:
http://arxiv.org/abs/1708.02476
Saliency detection, finding the most important parts of an image, has become increasingly popular in computer vision. In this paper, we introduce Hierarchical Cellular Automata (HCA) -- a temporally evolving model to intelligently detect salient obje
Externí odkaz:
http://arxiv.org/abs/1705.09425