Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Xiang, Jianfeng"'
Autor:
Wang, Ruicheng, Xu, Sicheng, Dai, Cassie, Xiang, Jianfeng, Deng, Yu, Tong, Xin, Yang, Jiaolong
We present MoGe, a powerful model for recovering 3D geometry from monocular open-domain images. Given a single image, our model directly predicts a 3D point map of the captured scene with an affine-invariant representation, which is agnostic to true
Externí odkaz:
http://arxiv.org/abs/2410.19115
We propose a novel image editing technique that enables 3D manipulations on single images, such as object rotation and translation. Existing 3D-aware image editing approaches typically rely on synthetic multi-view datasets for training specialized mo
Externí odkaz:
http://arxiv.org/abs/2403.11503
Previous animatable 3D-aware GANs for human generation have primarily focused on either the human head or full body. However, head-only videos are relatively uncommon in real life, and full body generation typically does not deal with facial expressi
Externí odkaz:
http://arxiv.org/abs/2309.02186
In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models. We formulate the 3D-aware image generation task as multiview 2D image set generation, and further to a sequential unconditional-conditional multi
Externí odkaz:
http://arxiv.org/abs/2303.17905
Recent works have shown that 3D-aware GANs trained on unstructured single image collections can generate multiview images of novel instances. The key underpinnings to achieve this are a 3D radiance field generator and a volume rendering process. Howe
Externí odkaz:
http://arxiv.org/abs/2206.07255
While class activation map (CAM) generated by image classification network has been widely used for weakly supervised object localization (WSOL) and semantic segmentation (WSSS), such classifiers usually focus on discriminative object regions. In thi
Externí odkaz:
http://arxiv.org/abs/2203.13505
3D-aware image generative modeling aims to generate 3D-consistent images with explicitly controllable camera poses. Recent works have shown promising results by training neural radiance field (NeRF) generators on unstructured 2D images, but still can
Externí odkaz:
http://arxiv.org/abs/2112.08867
Autor:
Xiang, Jianfeng, Wu, Xinrui, Liu, Wangrui, Wei, Huagen, Zhu, Zhu, Liu, Shifan, Song, Chengqi, Gu, Qiang, Wei, Shiyin, Zhang, Yichi
Publikováno v:
In Heliyon May 2023 9(5)
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Akademický článek
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