Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Recently, neural implicit surfaces learning by volume rendering has become popular for
multi-view reconstruction. However, one key challenge remains: existing approaches lack …

Implicit neural rendering techniques have shown promising results for novel view synthesis.
However, existing methods usually encode the entire scene as a whole, which is generally …

Abstract 3D reconstruction of scenes using multiple images, relying on robust
correspondence search and depth estimation, has been thoroughly studied for the two‐view …

Very recently neural implicit rendering techniques have been rapidly evolved and shown
great advantages in novel view synthesis and 3D scene reconstruction. However, existing …

In this paper, we present TransMVSNet, based on our exploration of feature matching in
multi-view stereo (MVS). We analogize MVS back to its nature of a feature matching task and …

Despite the remarkable progress made by learning based stereo matching algorithms, one
key challenge remains unsolved. Current state-of-the-art stereo models are mostly based on …

Abstract Recent cascade Multi-View Stereo (MVS) methods can efficiently estimate high-
resolution depth maps through narrowing hypothesis ranges. However, previous methods …

We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for
high-resolution multi-view stereo. With high computation speed and low memory …

Depth estimation is solved as a regression or classification problem in existing learning-
based multi-view stereo methods. Although these two representations have recently …