Multi-view stereo reconstruction (MVS) in the wild requires to first estimate the camera
intrinsic and extrinsic parameters. These are usually tedious and cumbersome to obtain yet …

Three-dimensional reconstruction is a key technology employed to represent virtual reality in
the real world, which is valuable in computer vision. Large-scale 3D models have broad …

In the field of binocular stereo matching, remarkable progress has been made by iterative
methods like RAFT-Stereo and CREStereo. However, most of these methods lose …

Learning-based stereo matching techniques have made significant progress. However
existing methods inevitably lose geometrical structure information during the feature channel …

Recent advances in generative AI have unveiled significant potential for the creation of 3D
content. However current methods either apply a pre-trained 2D diffusion model with the …

In this paper, we propose a practical three-dimensional (3D) real-scene reconstruction
framework named Deep3D, which is paired with a deep learning based multi-view stereo …

In this paper, we propose a general deep learning based framework, named Sat-MVSF, to
perform three-dimensional (3D) reconstruction of the Earth's surface from multi-view optical …

An important objective in computer vision is to analyze multiple images and subsequently
reconstruct the shape and structure in 3D. Traditional multi-view 3D reconstruction …

Matching cost aggregation plays a fundamental role in learning-based multi-view stereo
networks. However directly aggregating adjacent costs can lead to suboptimal results due to …

We present a novel approach for synthesizing 3D talking heads with controllable emotion,
featuring enhanced lip synchronization and rendering quality. Despite significant progress in …