Results 21 to 30 of about 1,186,680 (282)
DTS-Depth: Real-Time Single-Image Depth Estimation Using Depth-to-Space Image Construction
Sensors, 2022 As most of the recent high-resolution depth-estimation algorithms are computationally so expensive that they cannot work in real time, the common solution is using a low-resolution input image to reduce the computational complexity.
Hatem Ibrahem +2 more
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SPLODE: Semi-Probabilistic Point and Line Odometry with Depth Estimation from RGB-D Camera Motion [PDF]
, 2017 Active depth cameras suffer from several limitations, which cause incomplete and noisy depth maps, and may consequently affect the performance of RGB-D Odometry.
Gao, Yang, Proença, Pedro F.
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A Review of Benchmark Datasets and Training Loss Functions in Neural Depth Estimation
IEEE Access, 2021 In many applications, such as robotic perception, scene understanding, augmented reality, 3D reconstruction, and medical image analysis, depth from images is a fundamentally ill-posed problem. The success of depth estimation models relies on assembling a
Faisal Khan +4 more
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Generalised Pose Estimation Using Depth [PDF]
, 2012 Estimating the pose of an object, be it articulated, deformable or rigid, is an important task, with applications ranging from Human-Computer Interaction to environmental understanding. The idea of a general pose estimation framework, capable of being rapidly retrained to suit a variety of tasks, is appealing.
Hadfield, Simon, Bowden, Richard
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Dynamic programming for multi-view disparity/depth estimation [PDF]
, 2006 novel algorithm for disparity/depth estimation from multi-view images is presented. A dynamic programming approach with window-based correlation and a novel cost function is proposed..
Anantrasirichai, N +3 more
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Depth Map Decomposition for Monocular Depth Estimation
, 2022 We propose a novel algorithm for monocular depth estimation that decomposes a metric depth map into a normalized depth map and scale features. The proposed network is composed of a shared encoder and three decoders, called G-Net, N-Net, and M-Net, which estimate gradient maps, a normalized depth map, and a metric depth map, respectively.
Jinyoung Jun +3 more
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Zoom motion estimation for color and depth videos using depth information
EURASIP Journal on Image and Video Processing, 2020 In this paper, two methods of zoom motion estimation for color and depth videos by using depth information are proposed. Color and depth videos are independently estimated for zoom motion. Zoom for color video is scaled by spatial domain, and depth video
Soon-kak Kwon, Dong-seok Lee
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RA-Depth: Resolution Adaptive Self-supervised Monocular Depth Estimation
, 2022 Existing self-supervised monocular depth estimation methods can get rid of expensive annotations and achieve promising results. However, these methods suffer from severe performance degradation when directly adopting a model trained on a fixed resolution to evaluate at other different resolutions.
He, Mu +5 more
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Single image depth estimation: An overview [PDF]
Digital Signal Processing, 2022 We review solutions to the problem of depth estimation, arguably the most important subtask in scene understanding. We focus on the single image depth estimation problem. Due to its properties, the single image depth estimation problem is currently best tackled with machine learning methods, most successfully with convolutional neural networks.
Alican Mertan +2 more
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Multi-Sensor Fusion Self-Supervised Deep Odometry and Depth Estimation
Remote Sensing, 2022 This paper presents a new deep visual-inertial odometry and depth estimation framework for improving the accuracy of depth estimation and ego-motion from image sequences and inertial measurement unit (IMU) raw data.
Yingcai Wan +4 more
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