Y Ming, X Meng, C Fan, H Yu - Neurocomputing, 2021 - Elsevier
Depth estimation is a classic task in computer vision, which is of great significance for many applications such as augmented reality, target tracking and autonomous driving. Traditional …
Z Teed, J Deng - Advances in neural information …, 2021 - proceedings.neurips.cc
We introduce DROID-SLAM, a new deep learning based SLAM system. DROID-SLAM consists of recurrent iterative updates of camera pose and pixelwise depth through a Dense …
J Sun, Z Shen, Y Wang, H Bao… - Proceedings of the …, 2021 - openaccess.thecvf.com
We present a novel method for local image feature matching. Instead of performing image feature detection, description, and matching sequentially, we propose to first establish pixel …
X Wang, R Zhang, C Shen… - Proceedings of the …, 2021 - openaccess.thecvf.com
To date, most existing self-supervised learning methods are designed and optimized for image classification. These pre-trained models can be sub-optimal for dense prediction …
As a fundamental and critical task in various visual applications, image matching can identify then correspond the same or similar structure/content from two or more images. Over the …
C Choy, J Park, V Koltun - Proceedings of the IEEE/CVF …, 2019 - openaccess.thecvf.com
Extracting geometric features from 3D scans or point clouds is the first step in applications such as registration, reconstruction, and tracking. State-of-the-art methods require …
J Revaud, C De Souza… - Advances in neural …, 2019 - proceedings.neurips.cc
Interest point detection and local feature description are fundamental steps in many computer vision applications. Classical approaches are based on a detect-then-describe …
We present a general framework for exemplar-based image translation, which synthesizes a photo-realistic image from the input in a distinct domain (eg, semantic segmentation mask …
In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions. We propose an approach where a single convolutional neural …