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Perceptual Monocular Depth Estimation
Neural Processing Letters, 2021Monocular depth estimation (MDE), which is the task of using a single image to predict scene depths, has gained considerable interest, in large part owing to the popularity of applying deep learning methods to solve “computer vision problems”. Monocular cues provide sufficient data for humans to instantaneously extract an understanding of scene ...
Janice Pan, Alan C. Bovik
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Fast Monocular Depth Estimation on an FPGA
2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2020Depth sensing is crucial for understanding 3D scenes on embedded systems such as home robots, self-driving cars, and drones. Monocular depth estimation which gives pixel-wise depth from a general camera, has attracted attention in recent years, due to the reliability, low-cost and small area requirement.
Youki Sada +5 more
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Monocular depth estimation with SPN loss
Image and Vision Computing, 2020Abstract Understanding the 3D space is crucial for autonomous vehicles for planning and navigation. Traditionally autonomous vehicles use LiDAR sensor to 3D map its environment. LiDAR sensor data are often noisy and sparse making it not fully reliable for real-time applications like autonomous driving, thus redundant such sensors are used for the ...
Alwyn Mathew, Jimson Mathew
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Geometric Pretraining for Monocular Depth Estimation
2020 IEEE International Conference on Robotics and Automation (ICRA), 2020ImageNet-pretrained networks have been widely used in transfer learning for monocular depth estimation. These pretrained networks are trained with classification losses for which only semantic information is exploited while spatial information is ignored. However, both semantic and spatial information is important for per-pixel depth estimation.
Kaixuan Wang +4 more
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A Synopsis of Monocular Depth Estimation
2021Depth information is necessary for automated devices or software to accomplish tasks which require the knowledge of the surrounding environment without error. Monocular depth estimation uses a single 2D image to estimate depth, which makes it an exigent method. However, recent studies in monocular depth estimation based on convolutional neural networks
Shubham Chaudhari +3 more
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Monocular Depth Estimation Using Relative Depth Maps
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019We propose a novel algorithm for monocular depth estimation using relative depth maps. First, using a convolutional neural network, we estimate relative depths between pairs of regions, as well as ordinary depths, at various scales. Second, we restore relative depth maps from selectively estimated data based on the rank-1 property of pairwise ...
Jaehan Lee, Chang-Su Kim 0001
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Densely Connecting Depth Maps for Monocular Depth Estimation
2020Predicting depth map from a single RGB image is beneficial for many three-dimensional applications. Although recent monocular depth estimation methods have achieved impressive accuracy, the preference on high-level features or low-level features prevents them from balancing sharpness and fidelity of depth maps.
Jinqing Zhang +4 more
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Monocular Depth Estimation: A Survey
IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society, 2023Dong Wang 0051 +5 more
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Sparse depth densification for monocular depth estimation
Multimedia Tools and Applications, 2023Zhen Liang +3 more
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