Results 41 to 50 of about 1,194,643 (283)
Sensors, 2021 As one of the key requirements for underwater exploration, underwater depth map estimation is of great importance in underwater vision research. Although significant progress has been achieved in the fields of image-to-image translation and depth map ...
Qi Zhao +3 more
doaj +1 more source
Aperture Supervision for Monocular Depth Estimation
, 2018 We present a novel method to train machine learning algorithms to estimate scene depths from a single image, by using the information provided by a camera's aperture as supervision.
Barron, Jonathan T. +4 more
core +1 more source
Unsupervised Learning of Depth and Ego-Motion from Video
, 2017 We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences. We achieve this by simultaneously training depth and camera pose estimation networks using the task of view ...
Brown, Matthew +3 more
core +1 more source
, 2018 Most of the existing deep learning-based methods for 3D hand and human pose estimation from a single depth map are based on a common framework that takes a 2D depth map and directly regresses the 3D coordinates of keypoints, such as hand or human body ...
Chang, Ju Yong +2 more
core +1 more source
Joint Blind Motion Deblurring and Depth Estimation of Light Field
, 2018 Removing camera motion blur from a single light field is a challenging task since it is highly ill-posed inverse problem. The problem becomes even worse when blur kernel varies spatially due to scene depth variation and high-order camera motion.
A Beck +12 more
core +1 more source
Learning sparse representations of depth [PDF]
, 2011 This paper introduces a new method for learning and inferring sparse representations of depth (disparity) maps. The proposed algorithm relaxes the usual assumption of the stationary noise model in sparse coding.
Culpepper, Benjamin J. +2 more
core +1 more source
, 2017 We study the problem of single-image depth estimation for images in the wild. We collect human annotated surface normals and use them to train a neural network that directly predicts pixel-wise depth. We propose two novel loss functions for training with
Chen, Weifeng, Deng, Jia, Xiang, Donglai
core +1 more source
Estimating Tukey depth using incremental quantile estimators
Pattern Recognition, 2022 The concept of depth represents methods to measure how deep an arbitrary point is positioned in a dataset and can be seen as the opposite of outlyingness. It has proved very useful and a wide range of methods have been developed based on the concept.
Hammer, Hugo Lewi +2 more
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT End‐of‐life conversations with adolescents and young adults (AYAs) with cancer rarely occur without the guidance of healthcare professionals. As a part of the ‘Difficult Discussions’ study, focused on palliative care and advance care planning discussions with AYAs with cancer, we investigated the factors that healthcare professionals identify ...
Justine Lee +9 more
wiley +1 more source
Sensors, 2022 Light field (LF) image depth estimation is a critical technique for LF-related applications such as 3D reconstruction, target detection, and tracking.
Ming Gao +4 more
doaj +1 more source