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Monocular Depth Estimation

Monocular Depth Estimation is the task of estimating the depth value (distance relative to the camera) of each pixel given a single (monocular) RGB image. This challenging task is a key prerequisite for determining scene understanding for applications such as 3D scene reconstruction, autonomous driving, and AR. State-of-the-art methods usually fall into one of two categories: designing a complex network that is powerful enough to directly regress the depth map, or splitting the input into bins or windows to reduce computational complexity. The most popular benchmarks are the KITTI and NYUv2 datasets. Models are typically evaluated using RMSE or absolute relative error.

Source: Defocus Deblurring Using Dual-Pixel Data

Papers

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Showing 401–425 of 876 papers

TitleStatusHype
Automatic Discovery and Geotagging of Objects from Street View ImageryCode0
Monocular Depth Estimation Using Cues Inspired by Biological Vision SystemsCode0
AutoColor: Learned Light Power Control for Multi-Color HologramsCode0
Fast Scene Understanding for Autonomous DrivingCode0
Fast Robust Monocular Depth Estimation for Obstacle Detection with Fully Convolutional NetworksCode0
Monocular 3D Object Detection with Pseudo-LiDAR Point CloudCode0
On Robust Cross-View Consistency in Self-Supervised Monocular Depth EstimationCode0
FastDepth: Fast Monocular Depth Estimation on Embedded SystemsCode0
False Negative Reduction in Semantic Segmentation under Domain Shift using Depth EstimationCode0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
FA-Depth: Toward Fast and Accurate Self-supervised Monocular Depth EstimationCode0
Exploring Efficiency of Vision Transformers for Self-Supervised Monocular Depth EstimationCode0
Exploiting temporal consistency for real-time video depth estimationCode0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Maximum Likelihood Uncertainty Estimation: Robustness to OutliersCode0
Lightweight Monocular Depth Estimation Model by Joint End-to-End Filter pruningCode0
Attention-Based Depth Distillation with 3D-Aware Positional Encoding for Monocular 3D Object DetectionCode0
D4D: An RGBD diffusion model to boost monocular depth estimationCode0
METER: a mobile vision transformer architecture for monocular depth estimationCode0
D^3epth: Self-Supervised Depth Estimation with Dynamic Mask in Dynamic ScenesCode0
Estimating Depth from RGB and Sparse SensingCode0
Attention-based Context Aggregation Network for Monocular Depth EstimationCode0
Enhancing Monocular Depth Estimation with Multi-Source Auxiliary TasksCode0
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth EstimationCode0
Cut-and-Splat: Leveraging Gaussian Splatting for Synthetic Data GenerationCode0
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