GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo

1 code implementation • 11 Apr 2024 • Jiang Wu, Rui Li, Haofei Xu, Wenxun Zhao, Yu Zhu, Jinqiu Sun, Yanning Zhang

More specifically, we correspond and propagate adjacent costs to the reference pixel by leveraging the local geometric smoothness in conjunction with surface normals.

MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images

1 code implementation • 21 Mar 2024 • Yuedong Chen, Haofei Xu, Chuanxia Zheng, Bohan Zhuang, Marc Pollefeys, Andreas Geiger, Tat-Jen Cham, Jianfei Cai

We propose MVSplat, an efficient feed-forward 3D Gaussian Splatting model learned from sparse multi-view images.

3D Reconstruction Generalizable Novel View Synthesis +2

MuRF: Multi-Baseline Radiance Fields

1 code implementation • 7 Dec 2023 • Haofei Xu, Anpei Chen, Yuedong Chen, Christos Sakaridis, Yulun Zhang, Marc Pollefeys, Andreas Geiger, Fisher Yu

We present Multi-Baseline Radiance Fields (MuRF), a general feed-forward approach to solving sparse view synthesis under multiple different baseline settings (small and large baselines, and different number of input views).

Zero-shot Generalization

Explicit Correspondence Matching for Generalizable Neural Radiance Fields

1 code implementation • 24 Apr 2023 • Yuedong Chen, Haofei Xu, Qianyi Wu, Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai

The key to our approach lies in the explicitly modeled correspondence matching information, so as to provide the geometry prior to the prediction of NeRF color and density for volume rendering.

Novel View Synthesis

Unifying Flow, Stereo and Depth Estimation

1 code implementation • 10 Nov 2022 • Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, Fisher Yu, DaCheng Tao, Andreas Geiger

We present a unified formulation and model for three motion and 3D perception tasks: optical flow, rectified stereo matching and unrectified stereo depth estimation from posed images.

Optical Flow Estimation Stereo Depth Estimation +1

GMFlow: Learning Optical Flow via Global Matching

4 code implementations • CVPR 2022 • Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, DaCheng Tao

Learning-based optical flow estimation has been dominated with the pipeline of cost volume with convolutions for flow regression, which is inherently limited to local correlations and thus is hard to address the long-standing challenge of large displacements.

Optical Flow Estimation regression

High-Resolution Optical Flow from 1D Attention and Correlation

1 code implementation • ICCV 2021 • Haofei Xu, Jiaolong Yang, Jianfei Cai, Juyong Zhang, Xin Tong

Optical flow is inherently a 2D search problem, and thus the computational complexity grows quadratically with respect to the search window, making large displacements matching infeasible for high-resolution images.

4k Optical Flow Estimation +1

Recurrent Multi-view Alignment Network for Unsupervised Surface Registration

1 code implementation • CVPR 2021 • Wanquan Feng, Juyong Zhang, Hongrui Cai, Haofei Xu, Junhui Hou, Hujun Bao

Learning non-rigid registration in an end-to-end manner is challenging due to the inherent high degrees of freedom and the lack of labeled training data.

Deformable Object Manipulation Neural Rendering +1

AANet: Adaptive Aggregation Network for Efficient Stereo Matching

1 code implementation • CVPR 2020 • Haofei Xu, Juyong Zhang

Despite the remarkable progress made by learning based stereo matching algorithms, one key challenge remains unsolved.

Scene Flow Estimation Stereo Disparity Estimation +1

Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos

1 code implementation • 26 Feb 2019 • Haofei Xu, Jianmin Zheng, Jianfei Cai, Juyong Zhang

In this paper, we propose a new learning based method consisting of DepthNet, PoseNet and Region Deformer Networks (RDN) to estimate depth from unconstrained monocular videos without ground truth supervision.

Depth Estimation