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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 451–475 of 876 papers

TitleStatusHype
Self-distilled Feature Aggregation for Self-supervised Monocular Depth EstimationCode1
BiFuse++: Self-supervised and Efficient Bi-projection Fusion for 360 Depth EstimationCode1
LiteDepth: Digging into Fast and Accurate Depth Estimation on Mobile DevicesCode1
Rethinking Skip Connections in Encoder-decoder Networks for Monocular Depth Estimation—0
Dense Depth Distillation with Out-of-Distribution Simulated Images—0
Depth Map Decomposition for Monocular Depth EstimationCode1
DepthFake: a depth-based strategy for detecting Deepfake videos—0
Multi-task Learning for Monocular Depth and Defocus Estimations with Real ImagesCode0
An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of MarsCode0
MonoViT: Self-Supervised Monocular Depth Estimation with a Vision TransformerCode1
TransDSSL: Transformer based Depth Estimation via Self-Supervised LearningCode1
Gradient-based Uncertainty for Monocular Depth EstimationCode1
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that MatterCode1
Learning Feature Decomposition for Domain Adaptive Monocular Depth Estimation—0
RA-Depth: Resolution Adaptive Self-Supervised Monocular Depth EstimationCode1
Latent Discriminant deterministic UncertaintyCode1
Focal-WNet: An Architecture Unifying Convolution and Attention for Depth EstimationCode0
MonoIndoor++:Towards Better Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments—0
Adversarial Attacks on Monocular Pose EstimationCode0
Physical Attack on Monocular Depth Estimation with Optimal Adversarial PatchesCode1
Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular Depth Estimation by Integrating IMU Motion DynamicsCode2
Depthformer : Multiscale Vision Transformer For Monocular Depth Estimation With Local Global Information FusionCode1
BlindSpotNet: Seeing Where We Cannot See—0
False Negative Reduction in Semantic Segmentation under Domain Shift using Depth EstimationCode0
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning—0
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