105 citations · 151 across the 17 of their papers we have counts for
6 papers · 1 filter
DynIBaR: Neural Dynamic Image-Based Rendering
Zhengqi Li, Qianqian Wang, Forrester Cole +2
We address the problem of synthesizing novel views from a monocular video depicting a complex dynamic scene. State-of-the-art methods based on temporally varying Neural Radiance Fi…
InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images
Zhengqi Li, Qianqian Wang, Noah Snavely +1
We present a method for learning to generate unbounded flythrough videos of natural scenes starting from a single view, where this capability is learned from a collection of single…
Neural 3D Reconstruction in the Wild
Jiaming Sun, Xi Chen, Qianqian Wang +4
We are witnessing an explosion of neural implicit representations in computer vision and graphics. Their applicability has recently expanded beyond tasks such as shape generation a…
3D Moments from Near-Duplicate Photos
Qianqian Wang, Zhengqi Li, David Salesin +3
We introduce 3D Moments, a new computational photography effect. As input we take a pair of near-duplicate photos, i.e., photos of moving subjects from similar viewpoints, common i…
Deformable Sprites for Unsupervised Video Decomposition
Vickie Ye, Zhengqi Li, Richard Tucker +2
We describe a method to extract persistent elements of a dynamic scene from an input video. We represent each scene element as a \emph{Deformable Sprite} consisting of three compon…
IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images
Kai Zhang, Fujun Luan, Zhengqi Li +1
We propose a neural inverse rendering pipeline called IRON that operates on photometric images and outputs high-quality 3D content in the format of triangle meshes and material tex…