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 601–625 of 2454 papers

Title	Date	Tasks	Status	Hype
Differentiable Diffusion for Dense Depth Estimation from Multi-view Images	Jun 16, 2021	Depth Estimation	CodeCode Available	1
ChiTransformer:Towards Reliable Stereo from Cues	Mar 9, 2022	Depth EstimationRetrieval	CodeCode Available	1
Chitransformer: Towards Reliable Stereo From Cues	Jan 1, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Learning Stereo from Single Images	Aug 4, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text Alignment	Dec 13, 2023	DecoderDepth Estimation	CodeCode Available	1
Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression Network	Jul 15, 2021	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation	Sep 26, 2021	Data AugmentationDepth Estimation	CodeCode Available	1
Depth Estimation from Monocular Images and Sparse Radar Data	Sep 30, 2020	Depth Estimation	CodeCode Available	1
Depth Estimation From Indoor Panoramas With Neural Scene Representation	Jan 1, 2023	Depth EstimationPosition	CodeCode Available	1
EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting	May 23, 2024	3D ReconstructionDepth Estimation	CodeCode Available	1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning	Oct 3, 2022	ClusteringDepth Estimation	CodeCode Available	1
Lifelong-MonoDepth: Lifelong Learning for Multi-Domain Monocular Metric Depth Estimation	Mar 9, 2023	Autonomous DrivingDepth Estimation	CodeCode Available	1
Digging into contrastive learning for robust depth estimation with diffusion models	Apr 15, 2024	Contrastive LearningDenoising	CodeCode Available	1
Digging Into Self-Supervised Monocular Depth Estimation	Jun 4, 2018	Camera Pose EstimationDepth Estimation	CodeCode Available	1
LiRCDepth: Lightweight Radar-Camera Depth Estimation via Knowledge Distillation and Uncertainty Guidance	Dec 20, 2024	Computational EfficiencyDepth Estimation	CodeCode Available	1
Digging Into Uncertainty-based Pseudo-label for Robust Stereo Matching	Jul 31, 2023	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Estimating Image Depth in the Comics Domain	Oct 7, 2021	Depth EstimationDepth Prediction	CodeCode Available	1
LocalBins: Improving Depth Estimation by Learning Local Distributions	Mar 28, 2022	AllDecoder	CodeCode Available	1
ES-Net: An Efficient Stereo Matching Network	Mar 5, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	1
Depth estimation from 4D light field videos	Dec 5, 2020	Depth EstimationDisparity Estimation	CodeCode Available	1
DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse points	Mar 19, 2020	Depth EstimationInterest Point Detection	CodeCode Available	1
Maximizing Self-supervision from Thermal Image for Effective Self-supervised Learning of Depth and Ego-motion	Jan 12, 2022	Depth EstimationSelf-Supervised Learning	CodeCode Available	1
A Practical Stereo Depth System for Smart Glasses	Nov 19, 2022	CPUDepth Estimation	CodeCode Available	1
EPI-based Oriented Relation Networks for Light Field Depth Estimation	Jul 9, 2020	Data AugmentationDepth Estimation	CodeCode Available	1
Event-based Stereo Depth Estimation from Ego-motion using Ray Density Fusion	Oct 17, 2022	Depth EstimationStereo Depth Estimation	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