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of 8
pro vyhledávání: '"Po, Ryan"'
Autor:
Malik, Anagh, Juravsky, Noah, Po, Ryan, Wetzstein, Gordon, Kutulakos, Kiriakos N., Lindell, David B.
We present an imaging and neural rendering technique that seeks to synthesize videos of light propagating through a scene from novel, moving camera viewpoints. Our approach relies on a new ultrafast imaging setup to capture a first-of-its kind, multi
Externí odkaz:
http://arxiv.org/abs/2404.06493
Customization techniques for text-to-image models have paved the way for a wide range of previously unattainable applications, enabling the generation of specific concepts across diverse contexts and styles. While existing methods facilitate high-fid
Externí odkaz:
http://arxiv.org/abs/2312.02432
Autor:
Po, Ryan, Yifan, Wang, Golyanik, Vladislav, Aberman, Kfir, Barron, Jonathan T., Bermano, Amit H., Chan, Eric Ryan, Dekel, Tali, Holynski, Aleksander, Kanazawa, Angjoo, Liu, C. Karen, Liu, Lingjie, Mildenhall, Ben, Nießner, Matthias, Ommer, Björn, Theobalt, Christian, Wonka, Peter, Wetzstein, Gordon
The field of visual computing is rapidly advancing due to the emergence of generative artificial intelligence (AI), which unlocks unprecedented capabilities for the generation, editing, and reconstruction of images, videos, and 3D scenes. In these do
Externí odkaz:
http://arxiv.org/abs/2310.07204
Neural radiance fields (NeRFs) have emerged as an effective method for novel-view synthesis and 3D scene reconstruction. However, conventional training methods require access to all training views during scene optimization. This assumption may be pro
Externí odkaz:
http://arxiv.org/abs/2309.01811
Autor:
Po, Ryan, Wetzstein, Gordon
Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level generation. W
Externí odkaz:
http://arxiv.org/abs/2303.12218
Diffusion models have emerged as the state-of-the-art for image generation, among other tasks. Here, we present an efficient diffusion-based model for 3D-aware generation of neural fields. Our approach pre-processes training data, such as ShapeNet me
Externí odkaz:
http://arxiv.org/abs/2211.16677
Single-photon avalanche diodes (SPADs) are growing in popularity for depth sensing tasks. However, SPADs still struggle in the presence of high ambient light due to the effects of pile-up. Conventional techniques leverage fixed or asynchronous gating
Externí odkaz:
http://arxiv.org/abs/2111.15047
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Single-photon avalanche diodes (SPADs) are growing in popularity for depth sensing tasks. However, SPADs still struggle in the presence of high ambient light due to the effects of pile-up. Conventional techniques leverage fixed or asynchronous gating