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 851–875 of 2454 papers

Title	Date	Tasks	Status	Score
Mutli-View 3D Reconstruction using Knowledge Distillation	Dec 2, 2024	3D ReconstructionDepth Estimation	CodeCode Available	5
MVDepthNet: Real-time Multiview Depth Estimation Neural Network	Jul 23, 2018	Data AugmentationDecoder	CodeCode Available	5
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting	Jul 6, 2021	3D Object DetectionAutonomous Driving	CodeCode Available	5
Multiview Detection with Cardboard Human Modeling	Jul 5, 2022	Depth EstimationMultiview Detection	CodeCode Available	5
Co-SemDepth: Fast Joint Semantic Segmentation and Depth Estimation on Aerial Images	Mar 23, 2025	Autonomous NavigationDepth Estimation	CodeCode Available	5
Correlation of Object Detection Performance with Visual Saliency and Depth Estimation	Nov 5, 2024	Depth EstimationDepth Prediction	CodeCode Available	5
Attention-based Context Aggregation Network for Monocular Depth Estimation	Jan 29, 2019	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation	Feb 27, 2018	3D Object Reconstruction3D Object Super-Resolution	CodeCode Available	5
Efficient Calisthenics Skills Classification through Foreground Instance Selection and Depth Estimation	Jul 16, 2025	ClassificationDepth Estimation	CodeCode Available	5
Focal-WNet: An Architecture Unifying Convolution and Attention for Depth Estimation	Jul 18, 2022	DecoderDepth Estimation	CodeCode Available	5
Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene Segmentation	Nov 25, 2022	Contrastive LearningDepth Estimation	CodeCode Available	5
Adversarial Attacks on Monocular Pose Estimation	Jul 14, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Multi-View Stereo by Temporal Nonparametric Fusion	Apr 12, 2019	DecoderDepth Estimation	CodeCode Available	5
Edge-Guided Occlusion Fading Reduction for a Light-Weighted Self-Supervised Monocular Depth Estimation	Nov 26, 2019	Depth EstimationGPU	CodeCode Available	5
Convolution kernel adaptation to calibrated fisheye	Feb 2, 2024	Depth EstimationSemantic Segmentation	CodeCode Available	5
Multi-task Learning for Monocular Depth and Defocus Estimations with Real Images	Aug 21, 2022	Defocus EstimationDepth Estimation	CodeCode Available	5
Multi-Task Meta Learning: learn how to adapt to unseen tasks	Oct 13, 2022	Depth EstimationEdge Detection	CodeCode Available	5
EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes	Nov 9, 2020	Depth EstimationDepth Prediction	CodeCode Available	5
Attacking Attention of Foundation Models Disrupts Downstream Tasks	Jun 3, 2025	Depth EstimationImage-text Retrieval	CodeCode Available	5
EDADepth: Enhanced Data Augmentation for Monocular Depth Estimation	Sep 10, 2024	Data AugmentationDepth Estimation	CodeCode Available	5
On the Benefit of Adversarial Training for Monocular Depth Estimation	Oct 29, 2019	Depth EstimationDepth Prediction	CodeCode Available	5
Multi-Modal Attention Networks for Enhanced Segmentation and Depth Estimation of Subsurface Defects in Pulse Thermography	Jan 17, 2025	Data AugmentationDepth Estimation	CodeCode Available	5
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation	Mar 3, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	5
Sea-ing in Low-light	Jan 1, 2025	Depth EstimationImage Restoration	CodeCode Available	5
Dynamic Filter Networks	May 31, 2016	Depth EstimationOptical Flow 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