CF-NeRF: Camera Parameter Free Neural Radiance Fields with Incremental Learning

no code implementations • 14 Dec 2023 • Qingsong Yan, Qiang Wang, Kaiyong Zhao, Jie Chen, Bo Li, Xiaowen Chu, Fei Deng

Neural Radiance Fields (NeRF) have demonstrated impressive performance in novel view synthesis.

Incremental Learning Novel View Synthesis

Rethinking Disparity: A Depth Range Free Multi-View Stereo Based on Disparity

1 code implementation • 30 Nov 2022 • Qingsong Yan, Qiang Wang, Kaiyong Zhao, Bo Li, Xiaowen Chu, Fei Deng

Existing learning-based multi-view stereo (MVS) methods rely on the depth range to build the 3D cost volume and may fail when the range is too large or unreliable.

SphereDepth: Panorama Depth Estimation from Spherical Domain

no code implementations • 29 Aug 2022 • Qingsong Yan, Qiang Wang, Kaiyong Zhao, Bo Li, Xiaowen Chu, Fei Deng

The panorama image can simultaneously demonstrate complete information of the surrounding environment and has many advantages in virtual tourism, games, robotics, etc.

Depth Estimation

RC-MVSNet: Unsupervised Multi-View Stereo with Neural Rendering

1 code implementation • 8 Mar 2022 • Di Chang, Aljaž Božič, Tong Zhang, Qingsong Yan, Yingcong Chen, Sabine Süsstrunk, Matthias Nießner

Finding accurate correspondences among different views is the Achilles' heel of unsupervised Multi-View Stereo (MVS).

Neural Rendering

IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

1 code implementation • 20 Dec 2019 • Qiang Wang, Shizhen Zheng, Qingsong Yan, Fei Deng, Kaiyong Zhao, Xiaowen Chu

Besides, we present DTN-Net, a two-stage deep model for surface normal estimation.

Disparity Estimation Scene Understanding +1