Deep learning technology has made great progress in multi-view 3D reconstruction tasks. At
present, the mainstream solutions adopt different ways to fusion the features from several …

In recent years, many video tasks have achieved breakthroughs by utilizing the vision
transformer and establishing spatial-temporal decoupling for feature extraction. Although …

Abstract 3D reconstruction is a long‐standing problem. Recently, a number of studies have
emerged that utilize transformers for 3D reconstruction, and these approaches have …

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 …

The widespread use of smartphones and other low-cost equipment as recording devices,
the massive growth in bandwidth, and the ever-growing demand for new applications with …

Reconstructing 3D structures from non-overlapping multi-view images is a crucial task in the
field of 3D computer vision, since it is difficult to establish feature correspondences and infer …

There has emerged substantial research in addressing single-view 3D reconstruction and
the majority of the state-of-the-art implicit methods employ CNNs as the backbone network …

We study the problem of object reconstruction in a multi-agent collaboration scenario.
Specifically, we focus on the reconstruction of specific goals through several cooperative …

Reconstructing texture-less surfaces poses unique challenges in computer vision, primarily
due to the lack of specialized datasets that cater to the nuanced needs of depth and normals …

We introduce 3D-COCO, an extension of the original MS-COCO dataset providing 3D
models and 2D-3D alignment annotations. 3D-COCO was designed to achieve computer …