205 citations · 728 across the 34 of their papers we have counts for
6 papers · 1 filter
Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
Mengyu Chu, Lingjie Liu, Quan Zheng +4
High-fidelity reconstruction of fluids from sparse multiview RGB videos remains a formidable challenge due to the complexity of the underlying physics as well as complex occlusion…
Advances in Neural Rendering
Ayush Tewari, Justus Thies, Ben Mildenhall +14
Synthesizing photo-realistic images and videos is at the heart of computer graphics and has been the focus of decades of research. Traditionally, synthetic images of a scene are ge…
CurveFusion: Reconstructing Thin Structures from RGBD Sequences
Lingjie Liu, Nenglun Chen, Duygu Ceylan +3
We introduce CurveFusion, the first approach for high quality scanning of thin structures at interactive rates using a handheld RGBD camera. Thin filament-like structures are mathe…
SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform
Cheng Lin, Lingjie Liu, Changjian Li +4
Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications. Exis…
Vid2Curve: Simultaneous Camera Motion Estimation and Thin Structure Reconstruction from an RGB Video
Peng Wang, Lingjie Liu, Nenglun Chen +3
Thin structures, such as wire-frame sculptures, fences, cables, power lines, and tree branches, are common in the real world. It is extremely challenging to acquire their 3D digita…
Neural Human Video Rendering by Learning Dynamic Textures and Rendering-to-Video Translation
Lingjie Liu, Weipeng Xu, Marc Habermann +5
Synthesizing realistic videos of humans using neural networks has been a popular alternative to the conventional graphics-based rendering pipeline due to its high efficiency. Exist…