most citedF-NeRF: Fast Neural Radiance Field Training with Free Camera Trajectories

11 citations · 25 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023★ 4 cited

PERF: Panoramic Neural Radiance Field from a Single Panorama

Guangcong Wang, Peng Wang, Zhaoxi Chen +3

Neural Radiance Field (NeRF) has achieved substantial progress in novel view synthesis given multi-view images. Recently, some works have attempted to train a NeRF from a single im…

cs.CV2023★ 3 cited

NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects from Multiview Images

Yuan Liu, Peng Wang, Cheng Lin +5

We present a neural rendering-based method called NeRO for reconstructing the geometry and the BRDF of reflective objects from multiview images captured in an unknown environment.…

cs.CV2023★ 11 cited

F-NeRF: Fast Neural Radiance Field Training with Free Camera Trajectories

Peng Wang, Yuan Liu, Zhaoxi Chen +5

This paper presents a novel grid-based NeRF called F2-NeRF (Fast-Free-NeRF) for novel view synthesis, which enables arbitrary input camera trajectories and only costs a few minutes…

cs.CV2022

Batch-based Model Registration for Fast 3D Sherd Reconstruction

Jiepeng Wang, Congyi Zhang, Peng Wang +4

3D reconstruction techniques have widely been used for digital documentation of archaeological fragments. However, efficient digital capture of fragments remains as a challenge. In…

cs.CV2022★ 6 cited

SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Views

Xiaoxiao Long, Cheng Lin, Peng Wang +2

We introduce SparseNeuS, a novel neural rendering based method for the task of surface reconstruction from multi-view images. This task becomes more difficult when only sparse imag…

cs.CV2022★ 1 cited

Progressively-connected Light Field Network for Efficient View Synthesis

Peng Wang, Yuan Liu, Guying Lin +4

This paper presents a Progressively-connected Light Field network (ProLiF), for the novel view synthesis of complex forward-facing scenes. ProLiF encodes a 4D light field, which al…