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How to Estimate Depth from a Single Image
Towards Data Science
In this post, we will illustrate how to load and visualize depth map data, run monocular depth estimation models, and evaluate depth predictions.
6 months ago
An efficient and accurate multi-level cascaded recurrent network for stereo matching
Nature
With the advent of Transformer-based convolutional neural networks, stereo matching algorithms have achieved state-of-the-art accuracy in...
4 months ago
Confidence-aware self-supervised learning for dense monocular depth estimation in dynamic laparoscopic scene
Nature
This paper tackles the challenge of accurate depth estimation from monocular laparoscopic images in dynamic surgical environments.
11 months ago
Intel Labs Advances Computer Vision Development with Two New AI Models
Unite.AI
Researchers at Intel Labs are addressing this issue by releasing two AI models for monocular depth estimation: one for visual-inertial depth estimation and one...
16 months ago
Monocular Depth Estimation to Predict Surface Reliefs of Mars | by Mattia Gatti
Towards Data Science
Several approaches to estimating surface elevation from a single image have been discussed in the literature. In a previous article,...
11 months ago
Research Guide for Depth Estimation with Deep Learning
KDnuggets
Depth estimation is a computer vision task designed to estimate depth from a 2D image. The task requires an input RGB image and outputs a...
57 months ago
Qualcomm AI Research Innovates 3D Perception Techniques
Forbes
Qualcomm AI Research has initially focused on 4 areas of 3D perception: depth estimation, pose estimation, object detection, and scene understanding.
24 months ago
BYOL —The Alternative to Contrastive Self-Supervised Learning
Towards Data Science
It provides an alternative to contrastive self-supervised learning techniques for representation learning removing the need for a large corpus of negative...
11 months ago
Where do we stand in AI for endoscopic image analysis? Deciphering gaps and future directions | npj Digital Medicine
Nature
Recent developments in deep learning have enabled data-driven algorithms that can reach human-level performance and beyond.
19 months ago
Deep learning-based robust positioning for all-weather autonomous driving
Nature
Here we propose a deep learning-based self-supervised approach for ego-motion estimation that is a robust and complementary localization solution under...
23 months ago