1 code implementation • 29 Feb 2024 • Ziyue Feng, Huangying Zhan, Zheng Chen, Qingan Yan, Xiangyu Xu, Changjiang Cai, Bing Li, Qilun Zhu, Yi Xu
We present NARUTO, a neural active reconstruction system that combines a hybrid neural representation with uncertainty learning, enabling high-fidelity surface reconstruction.
no code implementations • 30 Dec 2023 • Zheng Chen, Qingan Yan, Huangying Zhan, Changjiang Cai, Xiangyu Xu, Yuzhong Huang, Weihan Wang, Ziyue Feng, Lantao Liu, Yi Xu
Through extensive experiments, we demonstrate the effectiveness of PlanarNeRF in various scenarios and remarkable improvement over existing works.
no code implementations • 12 Apr 2023 • Xiangyu Xu, Lichang Chen, Changjiang Cai, Huangying Zhan, Qingan Yan, Pan Ji, Junsong Yuan, Heng Huang, Yi Xu
Direct optimization of interpolated features on multi-resolution voxel grids has emerged as a more efficient alternative to MLP-like modules.
no code implementations • 25 Oct 2022 • Zhiqi Zhang, Nitin Bansal, Changjiang Cai, Pan Ji, Qingan Yan, Xiangyu Xu, Yi Xu
To this end, we propose CLIP-FLow, a semi-supervised iterative pseudo-labeling framework to transfer the pretraining knowledge to the target real domain.
no code implementations • CVPR 2023 • Changjiang Cai, Pan Ji, Qingan Yan, Yi Xu
At the pixel level, we propose to break the symmetry of the Siamese network (which is typically used in MVS to extract image features) by introducing a transformer block to the reference image (but not to the source images).
no code implementations • 5 May 2022 • Qingan Yan, Pan Ji, Nitin Bansal, Yuxin Ma, Yuan Tian, Yi Xu
In this paper, we deal with the problem of monocular depth estimation for fisheye cameras in a self-supervised manner.
no code implementations • 5 May 2022 • Pan Ji, Yuan Tian, Qingan Yan, Yuxin Ma, Yi Xu
The CNN depth effectively bootstraps the back-end optimization of SLAM and meanwhile the CNN uncertainty adaptively weighs the contribution of each feature point to the back-end optimization.
no code implementations • 3 May 2022 • Pan Ji, Qingan Yan, Yuxin Ma, Yi Xu
We present a robust and accurate depth refinement system, named GeoRefine, for geometrically-consistent dense mapping from monocular sequences.
no code implementations • CVPR 2022 • Jiachen Liu, Pan Ji, Nitin Bansal, Changjiang Cai, Qingan Yan, Xiaolei Huang, Yi Xu
The semantic plane detection branch is based on a single-view plane detection framework but with differences.
1 code implementation • ECCV 2020 • Wenxiao Zhang, Qingan Yan, Chunxia Xiao
In this work, instead of using a global feature to recover the whole complete surface, we explore the functionality of multi-level features and aggregate different features to represent the known part and the missing part separately.
no code implementations • CVPR 2018 • Yanping Fu, Qingan Yan, Long Yang, Jie Liao, Chunxia Xiao
Acquiring realistic texture details for 3D models is important in 3D reconstruction.
1 code implementation • CVPR 2017 • Qingan Yan, Long Yang, Ling Zhang, Chunxia Xiao
A perennial problem in structure from motion (SfM) is visual ambiguity posed by repetitive structures.