Depth Estimation

Depth Estimation is the task of measuring the distance of each pixel relative to the camera. Depth is extracted from either monocular (single) or stereo (multiple views of a scene) images. Traditional methods use multi-view geometry to find the relationship between the images. Newer methods can directly estimate depth by minimizing the regression loss, or by learning to generate a novel view from a sequence. The most popular benchmarks are KITTI and NYUv2. Models are typically evaluated according to a RMS metric.

Source: DIODE: A Dense Indoor and Outdoor DEpth Dataset

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 701–725 of 2454 papers

Title	Date	Tasks	Status	Hype	Score
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenes	Oct 12, 2023	Autonomous DrivingDepth Estimation	CodeCode Available	1	5
Self-Distilled Depth Refinement with Noisy Poisson Fusion	Sep 26, 2024	Depth Estimation	CodeCode Available	1	5
Single-Image Depth Prediction Makes Feature Matching Easier	Aug 1, 2020	Depth EstimationDepth Prediction	CodeCode Available	1	5
TriStereoNet: A Trinocular Framework for Multi-baseline Disparity Estimation	Nov 24, 2021	Depth EstimationDisparity Estimation	CodeCode Available	1	5
Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervision	Mar 22, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	1	5
Edge-aware Bidirectional Diffusion for Dense Depth Estimation from Light Fields	Jul 7, 2021	Depth Estimation	CodeCode Available	1	5
Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction	Apr 22, 2020	Depth EstimationDepth Prediction	CodeCode Available	0	5
PU-Ray: Domain-Independent Point Cloud Upsampling via Ray Marching on Neural Implicit Surface	Oct 12, 2023	Autonomous DrivingDepth Estimation	CodeCode Available	0	5
Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation	Dec 6, 2019	3D Point Cloud Reconstruction3D Reconstruction	CodeCode Available	0	5
Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled Networks	Sep 17, 2019	Data AugmentationDepth Estimation	CodeCode Available	0	5
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving	Jun 14, 2019	3D Object Detection3D Object Detection From Stereo Images	CodeCode Available	0	5
3D Ken Burns Effect from a Single Image	Sep 12, 2019	Depth EstimationDepth Prediction	CodeCode Available	0	5
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture	Nov 18, 2014	Depth EstimationDepth Prediction	CodeCode Available	0	5
Pose Constraints for Consistent Self-supervised Monocular Depth and Ego-motion	Apr 18, 2023	Camera Pose EstimationDepth Estimation	CodeCode Available	0	5
An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of Mars	Aug 15, 2022	Depth EstimationGenerative Adversarial Network	CodeCode Available	0	5
Point Spread Function Estimation of Defocus	Mar 6, 2022	Depth Estimation	CodeCode Available	0	5
Precision Aquaculture: An Integrated Computer Vision and IoT Approach for Optimized Tilapia Feeding	Sep 13, 2024	Depth EstimationKeypoint Detection	CodeCode Available	0	5
Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic Segmentation	Oct 13, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	0	5
Plug-and-Play: Improve Depth Estimation via Sparse Data Propagation	Dec 20, 2018	Depth EstimationDepth Prediction	CodeCode Available	0	5
Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts	Mar 7, 2024	Depth Estimationregression	CodeCode Available	0	5
Dense Scene Reconstruction from Light-Field Images Affected by Rolling Shutter	Dec 4, 2024	Depth Estimation	CodeCode Available	0	5
PLADE-Net: Towards Pixel-Level Accuracy for Self-Supervised Single-View Depth Estimation with Neural Positional Encoding and Distilled Matting Loss	Mar 12, 2021	Depth EstimationImage Matting	CodeCode Available	0	5
Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios	Jun 21, 2019	Depth Estimation	CodeCode Available	0	5
Planar Prior Assisted PatchMatch Multi-View Stereo	Dec 26, 2019	Depth EstimationMulti-View 3D Reconstruction	CodeCode Available	0	5
PID4LaTe: a physics-informed deep learning model for lake multi-depth temperature prediction	Jun 24, 2024	Depth EstimationDepth Prediction	CodeCode Available	0	5

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All datasets Stanford2D3D Panoramic NYU-Depth V2 DCM eBDtheque ScanNetV2 Cityscapes test DIODE KITTI 2015 Mars DTM Estimation ScanNet 4D Light Field Dataset KITTI Eigen split

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	OmniDepth	RMSE	0.62	—	Unverified
2	SphereDepth	RMSE	0.45	—	Unverified
3	Jin et al.	RMSE	0.42	—	Unverified
4	BiFuse with fusion	RMSE	0.41	—	Unverified
5	HoHoNet (ResNet-101)	RMSE	0.38	—	Unverified
6	PanoDepth	RMSE	0.37	—	Unverified
7	BiFuse++	RMSE	0.37	—	Unverified
8	UniFuse with fusion	RMSE	0.37	—	Unverified
9	DisConv	RMSE	0.37	—	Unverified
10	SliceNet	RMSE	0.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	A2J	mAP	8.61	—	Unverified
2	PAD-Net	RMS	0.79	—	Unverified
3	MS-CRF	RMS	0.59	—	Unverified
4	DORN	RMS	0.51	—	Unverified
5	Freeform	RMS	0.43	—	Unverified
6	Optimized, freeform	RMS	0.43	—	Unverified
7	VNL	RMS	0.42	—	Unverified
8	BTS	RMS	0.41	—	Unverified
9	TransDepth (AGD+ ViT)	RMS	0.37	—	Unverified
10	AdaBins	RMS	0.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	T2Net	Abs Rel	0.35	—	Unverified
2	MIDAS	Abs Rel	0.31	—	Unverified
3	Bhattacharjee et al.	Abs Rel	0.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	T2Net	Abs Rel	0.49	—	Unverified
2	MIDAS	Abs Rel	0.42	—	Unverified
3	Bhattacharjee et al.	Abs Rel	0.38	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LeReS	absolute relative error	0.1	—	Unverified
2	DELTAS	absolute relative error	0.09	—	Unverified
3	Distill Any Depth	absolute relative error	0.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SDC-Depth	RMSE	6.92	—	Unverified
2	SwinMTL	RMSE	6.35	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AIP-Brown	Delta < 1.25	0.36	—	Unverified
2	LeRes	Delta < 1.25	0.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	H-Net (Ours)	Absolute relative error (AbsRel)	0.09	—	Unverified
2	H-Net (Ours) Full Eigen	Absolute relative error (AbsRel)	0.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GLPDepth	Delta < 1.25	0.43	—	Unverified
2	SRDINET (Model A)	Delta < 1.25	0.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Atlas (finetuned)	RMSE	0.17	—	Unverified
2	Atlas (plain)	RMSE	0.17	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LFattNet	BadPix(0.01)	17.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LightDepth	Number of parameters (M)	42.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniFuse	Abs Rel	0.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	X-TC (Cross-Task Consistency)	L1 error	1.63	—	Unverified