Generative artificial intelligence (AI) is a form of AI that can autonomously generate new
content, such as text, images, audio, and video. Generative AI provides innovative …

Estimating depth from single RGB images and videos is of widespread interest due to its
applications in many areas, including autonomous driving, 3D reconstruction, digital …

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 …

Self-supervised monocular depth estimation is an attractive solution that does not require
hard-to-source depth la-bels for training. Convolutional neural networks (CNNs) have …

Abstract Masked Image Modeling (MIM) has recently been established as a potent pre-
training paradigm. A pretext task is constructed by masking patches in an input image, and …

We introduce a novel framework for training deep stereo networks effortlessly and without
any ground-truth. By leveraging state-of-the-art neural rendering solutions, we generate …

We present a new loss function for joint disparity and uncertainty estimation in deep stereo
matching. Our work is motivated by the need for precise uncertainty estimates and the …

Due to the domain differences and unbalanced disparity distribution across multiple
datasets, current stereo matching approaches are commonly limited to a specific dataset …

This paper reports on the NTIRE 2024 challenge on HR Depth From images of Specular and
Transparent surfaces held in conjunction with the New Trends in Image Restoration and …

Despite stereo matching accuracy has greatly improved by deep learning in the last few
years, recovering sharp boundaries and high-resolution outputs efficiently remains …