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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 576–600 of 876 papers

TitleStatusHype
3D Object Aided Self-Supervised Monocular Depth Estimation—0
Attention-Based Depth Distillation with 3D-Aware Positional Encoding for Monocular 3D Object DetectionCode0
ObjCAViT: Improving Monocular Depth Estimation Using Natural Language Models And Image-Object Cross-AttentionCode0
Hybrid Transformer Based Feature Fusion for Self-Supervised Monocular Depth Estimation—0
Towards Comprehensive Representation Enhancement in Semantics-guided Self-supervised Monocular Depth Estimation—0
Photo-realistic Neural Domain Randomization—0
Hierarchical Normalization for Robust Monocular Depth Estimation—0
MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentation—0
Improving the Reliability for Confidence Estimation—0
Composite Learning for Robust and Effective Dense Predictions—0
Depth Is All You Need for Monocular 3D Detection—0
Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation—0
MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation—0
Lightweight Monocular Depth Estimation with an Edge Guided Network—0
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs—0
On Robust Cross-View Consistency in Self-Supervised Monocular Depth EstimationCode0
Rethinking Skip Connections in Encoder-decoder Networks for Monocular Depth Estimation—0
Dense Depth Distillation with Out-of-Distribution Simulated Images—0
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
Learning Feature Decomposition for Domain Adaptive Monocular Depth Estimation—0
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
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