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 1001–1025 of 2454 papers

Title	Date	Tasks	Status	Score
Learning Single Camera Depth Estimation using Dual-Pixels	Apr 11, 2019	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Learning to Adapt for Stereo	Apr 5, 2019	Autonomous DrivingDepth Estimation	CodeCode Available	5
CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth	Apr 3, 2019	3D Depth EstimationDepth Estimation	CodeCode Available	5
Learning Monocular Depth by Distilling Cross-domain Stereo Networks	Aug 20, 2018	Autonomous DrivingDepth Estimation	CodeCode Available	5
Learning monocular depth estimation infusing traditional stereo knowledge	Apr 8, 2019	Depth EstimationImage Generation	CodeCode Available	5
Learning monocular depth estimation with unsupervised trinocular assumptions	Aug 5, 2018	Depth EstimationImage Reconstruction	CodeCode Available	5
Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras	Apr 10, 2019	Depth EstimationDepth Prediction	CodeCode Available	5
CAD2RL: Real Single-Image Flight without a Single Real Image	Nov 13, 2016	3D geometryCollision Avoidance	CodeCode Available	5
Learning Multi-modal Information for Robust Light Field Depth Estimation	Apr 13, 2021	Depth Estimation	CodeCode Available	5
Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields	Feb 26, 2015	Depth Estimation	CodeCode Available	5
DepthFormer: Exploiting Long-Range Correlation and Local Information for Accurate Monocular Depth Estimation	Mar 27, 2022	Depth EstimationInductive Bias	CodeCode Available	5
A Neural Network for Detailed Human Depth Estimation from a Single Image	Oct 3, 2019	Depth Estimation	CodeCode Available	5
Learning Depth with Convolutional Spatial Propagation Network	Oct 4, 2018	Depth CompletionDepth Estimation	CodeCode Available	5
Learning Across Tasks and Domains	Apr 9, 2019	Depth EstimationDomain Adaptation	CodeCode Available	5
Learning Non-Volumetric Depth Fusion Using Successive Reprojections	Jun 1, 2019	3D ReconstructionDepth Estimation	CodeCode Available	5
Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network	Aug 1, 2018	Depth EstimationDepth Prediction	CodeCode Available	5
Joint Depth Estimation and Mixture of Rain Removal From a Single Image	Mar 31, 2023	Depth EstimationRain Removal	CodeCode Available	5
iToF-flow-based High Frame Rate Depth Imaging	Jan 1, 2024	Depth Estimation	CodeCode Available	5
Introducing a Class-Aware Metric for Monocular Depth Estimation: An Automotive Perspective	Sep 6, 2024	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Into the Fog: Evaluating Robustness of Multiple Object Tracking	Apr 12, 2024	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Investigating Neural Architectures by Synthetic Dataset Design	Apr 23, 2022	Depth Estimation	CodeCode Available	5
Visual Domain Adaptation for Monocular Depth Estimation on Resource-Constrained Hardware	Aug 5, 2021	Depth EstimationDomain Adaptation	CodeCode Available	5
Nighttime Stereo Depth Estimation using Joint Translation-Stereo Learning: Light Effects and Uninformative Regions	Sep 30, 2019	Depth EstimationStereo Depth Estimation	CodeCode Available	5
Indoor Depth Completion with Boundary Consistency and Self-Attention	Aug 22, 2019	Depth CompletionDepth Estimation	CodeCode Available	5
LCD: Learned Cross-Domain Descriptors for 2D-3D Matching	Nov 21, 2019	3D Point Cloud MatchingDepth Estimation	CodeCode Available	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