no code implementations • 27 May 2024 • Jiahui Lei, Yijia Weng, Adam Harley, Leonidas Guibas, Kostas Daniilidis
We introduce 4D Motion Scaffolds (MoSca), a neural information processing system designed to reconstruct and synthesize novel views of dynamic scenes from monocular videos captured casually in the wild.
no code implementations • 26 Mar 2024 • Yunzhou Song, Jiahui Lei, ZiYun Wang, Lingjie Liu, Kostas Daniilidis
We propose a novel test-time optimization approach for efficiently and robustly tracking any pixel at any time in a video.
no code implementations • 30 Nov 2023 • Agelos Kratimenos, Jiahui Lei, Kostas Daniilidis
We argue that the per-point motions of a dynamic scene can be decomposed into a small set of explicit or learned trajectories.
no code implementations • 27 Nov 2023 • Jiahui Lei, Yufu Wang, Georgios Pavlakos, Lingjie Liu, Kostas Daniilidis
We introduce Gaussian Articulated Template Model GART, an explicit, efficient, and expressive representation for non-rigid articulated subject capturing and rendering from monocular videos.
no code implementations • 25 May 2023 • Jiahui Lei, Congyue Deng, Bokui Shen, Leonidas Guibas, Kostas Daniilidis
We propose Neural 3D Articulation Prior (NAP), the first 3D deep generative model to synthesize 3D articulated object models.
no code implementations • CVPR 2023 • Jiahui Lei, Congyue Deng, Karl Schmeckpeper, Leonidas Guibas, Kostas Daniilidis
First, we introduce equivariant shape representations to this problem to eliminate the complexity induced by the variation in object configuration.
no code implementations • 30 Dec 2022 • Yinshuang Xu, Jiahui Lei, Kostas Daniilidis
We model the ray space, the domain of the light field, as a homogeneous space of $SE(3)$ and introduce the $SE(3)$-equivariant convolution in ray space.
no code implementations • 16 Jun 2022 • Yinshuang Xu, Jiahui Lei, Edgar Dobriban, Kostas Daniilidis
We present a unified derivation of kernels via the Fourier domain by leveraging the sparsity of Fourier coefficients of the lifted feature fields.
1 code implementation • CVPR 2022 • Jiahui Lei, Kostas Daniilidis
While neural representations for static 3D shapes are widely studied, representations for deformable surfaces are limited to be template-dependent or lack efficiency.
1 code implementation • ECCV 2020 • Jiahui Lei, Srinath Sridhar, Paul Guerrero, Minhyuk Sung, Niloy Mitra, Leonidas J. Guibas
We investigate the problem of learning to generate 3D parametric surface representations for novel object instances, as seen from one or more views.