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

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Showing 226–250 of 2454 papers

Title	Date	Tasks	Status	Hype
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception	Apr 15, 2025	Data AugmentationDenoising	CodeCode Available	1
Beyond Image to Depth: Improving Depth Prediction using Echoes	Mar 15, 2021	Depth EstimationDepth Prediction	CodeCode Available	1
Differentiable Diffusion for Dense Depth Estimation from Multi-view Images	Jun 16, 2021	Depth Estimation	CodeCode Available	1
All in Tokens: Unifying Output Space of Visual Tasks via Soft Token	Jan 5, 2023	AllDepth Estimation	CodeCode Available	1
Bi3D: Stereo Depth Estimation via Binary Classifications	May 14, 2020	Autonomous NavigationDepth Estimation	CodeCode Available	1
Bidirectional Attention Network for Monocular Depth Estimation	Sep 1, 2020	Depth EstimationMachine Translation	CodeCode Available	1
BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion	Jun 1, 2020	Depth Estimation	CodeCode Available	1
Digging into contrastive learning for robust depth estimation with diffusion models	Apr 15, 2024	Contrastive LearningDenoising	CodeCode Available	1
Energy-Efficient Adaptive 3D Sensing	Jan 1, 2023	Depth EstimationStereo Depth Estimation	CodeCode Available	1
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation	Oct 8, 2022	Data AugmentationDepth Estimation	CodeCode Available	1
AeDet: Azimuth-invariant Multi-view 3D Object Detection	Nov 22, 2022	3D Object DetectionDepth Estimation	CodeCode Available	1
EPI-based Oriented Relation Networks for Light Field Depth Estimation	Jul 9, 2020	Data AugmentationDepth Estimation	CodeCode Available	1
ES-Net: An Efficient Stereo Matching Network	Mar 5, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	1
A Concise but High-performing Network for Image Guided Depth Completion in Autonomous Driving	Jan 29, 2024	Autonomous DrivingDepth Completion	CodeCode Available	1
Can Language Understand Depth?	Jul 3, 2022	Depth Estimationimage-classification	CodeCode Available	1
Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation	Sep 26, 2021	Data AugmentationDepth Estimation	CodeCode Available	1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning	Oct 3, 2022	ClusteringDepth Estimation	CodeCode Available	1
Detecting Invisible People	Dec 15, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view Stereo	Jan 19, 2022	Depth Estimation	CodeCode Available	1
BodySLAM: A Generalized Monocular Visual SLAM Framework for Surgical Applications	Aug 6, 2024	3D ReconstructionDepth Estimation	CodeCode Available	1
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells	Oct 25, 2018	Depth EstimationDepth Prediction	CodeCode Available	1
CaFNet: A Confidence-Driven Framework for Radar Camera Depth Estimation	Jun 30, 2024	Autonomous DrivingDepth Estimation	CodeCode Available	1
DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries	Oct 13, 2021	3D Object DetectionAutonomous Driving	CodeCode Available	1
Digging Into Self-Supervised Monocular Depth Estimation	Jun 4, 2018	Camera Pose EstimationDepth Estimation	CodeCode Available	1
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation	Apr 28, 2021	Depth EstimationDepth Prediction	CodeCode Available	1

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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