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 576–600 of 2454 papers

Title	Date	Tasks	Status	Hype	Score
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation	Apr 28, 2021	Depth EstimationDepth Prediction	CodeCode Available	1	5
Does it work outside this benchmark? Introducing the Rigid Depth Constructor tool, depth validation dataset construction in rigid scenes for the masses	Mar 29, 2021	Depth EstimationDepth Prediction	CodeCode Available	1	5
Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks	Nov 26, 2020	Depth EstimationMixture-of-Experts	CodeCode Available	1	5
Brain Captioning: Decoding human brain activity into images and text	May 19, 2023	Brain DecodingDepth Estimation	CodeCode Available	1	5
Efficient Attention: Attention with Linear Complexities	Dec 4, 2018	Depth EstimationExtractive Text Summarization	CodeCode Available	1	5
Categorical Depth Distribution Network for Monocular 3D Object Detection	Mar 1, 2021	3D Object DetectionAutonomous Vehicles	CodeCode Available	1	5
On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks	Mar 26, 2023	Depth Estimation	CodeCode Available	1	5
3D-PL: Domain Adaptive Depth Estimation with 3D-aware Pseudo-Labeling	Sep 19, 2022	Depth EstimationDomain Adaptation	CodeCode Available	1	5
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation	Oct 8, 2022	Data AugmentationDepth Estimation	CodeCode Available	1	5
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells	Oct 25, 2018	Depth EstimationDepth Prediction	CodeCode Available	1	5
Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinement	Mar 29, 2020	Depth Estimation	CodeCode Available	1	5
CDGS: Confidence-Aware Depth Regularization for 3D Gaussian Splatting	Feb 20, 2025	3DGS3D Reconstruction	CodeCode Available	1	5
Feature-metric Loss for Self-supervised Learning of Depth and Egomotion	Jul 21, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1	5
Boundary-induced and scene-aggregated network for monocular depth prediction	Feb 26, 2021	Depth EstimationDepth Prediction	CodeCode Available	1	5
Detecting Invisible People	Dec 15, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1	5
DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data	Feb 3, 2020	Depth EstimationDepth Prediction	CodeCode Available	1	5
Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo	Apr 6, 2021	3D Multi-Person Pose Estimation3D Pose Estimation	CodeCode Available	1	5
Disparity Estimation Using a Quad-Pixel Sensor	Sep 1, 2024	Depth EstimationDisparity Estimation	CodeCode Available	1	5
DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction	Sep 14, 2022	Depth Estimation	CodeCode Available	1	5
Flare-Free Vision: Empowering Uformer with Depth Insights	Apr 1, 2024	Depth EstimationFlare Removal	CodeCode Available	1	5
FLSea: Underwater Visual-Inertial and Stereo-Vision Forward-Looking Datasets	Feb 24, 2023	3D ReconstructionDepth Estimation	CodeCode Available	1	5
Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression Network	Jul 15, 2021	Depth EstimationMonocular Depth Estimation	CodeCode Available	1	5
RePoseD: Efficient Relative Pose Estimation With Known Depth Information	Jan 13, 2025	Camera Pose EstimationDepth Estimation	CodeCode Available	1	5
Automated Distance Estimation for Wildlife Camera Trapping	Feb 9, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1	5
Depth Estimation from Monocular Images and Sparse Radar Data	Sep 30, 2020	Depth Estimation	CodeCode Available	1	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