no code implementations • 20 Dec 2023 • Weijia Mao, Yan-Pei Cao, Jia-Wei Liu, Zhongcong Xu, Mike Zheng Shou
Previous methods using 2D diffusion priors to optimize neural radiance fields for generating room-scale scenes have shown unsatisfactory quality.
no code implementations • 16 Oct 2023 • Jia-Wei Liu, Yan-Pei Cao, Jay Zhangjie Wu, Weijia Mao, YuChao Gu, Rui Zhao, Jussi Keppo, Ying Shan, Mike Zheng Shou
To overcome this, we propose to introduce the dynamic Neural Radiance Fields (NeRF) as the innovative video representation, where the editing can be performed in the 3D spaces and propagated to the entire video via the deformation field.
1 code implementation • 31 May 2022 • Jia-Wei Liu, Yan-Pei Cao, Weijia Mao, Wenqiao Zhang, David Junhao Zhang, Jussi Keppo, Ying Shan, XiaoHu Qie, Mike Zheng Shou
In this paper, we present DeVRF, a novel representation to accelerate learning dynamic radiance fields.
1 code implementation • 31 May 2022 • Satoshi Tsutsui, Weijia Mao, Sijing Lin, Yunyi Zhu, Murong Ma, Mike Zheng Shou
Based on these observations, we propose a method to use both NeRF and 3DMM to synthesize a high-fidelity novel view of a scene with a face.