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 1876–1900 of 2454 papers

Title	Date	Tasks	Status	Hype
Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance	Jul 14, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
360^ Depth Estimation from Multiple Fisheye Images with Origami Crown Representation of Icosahedron	Jul 14, 2020	Depth EstimationGPU	CodeCode Available	1
UnRectDepthNet: Self-Supervised Monocular Depth Estimation using a Generic Framework for Handling Common Camera Distortion Models	Jul 13, 2020	Depth Estimationdistortion correction	—Unverified	0
AI Playground: Unreal Engine-based Data Ablation Tool for Deep Learning	Jul 13, 2020	Data AblationDepth Estimation	CodeCode Available	1
Continual Adaptation for Deep Stereo	Jul 10, 2020	Depth Estimation	CodeCode Available	1
EPI-based Oriented Relation Networks for Light Field Depth Estimation	Jul 9, 2020	Data AugmentationDepth Estimation	CodeCode Available	1
Camera Pose Matters: Improving Depth Prediction by Mitigating Pose Distribution Bias	Jul 8, 2020	Data AugmentationDepth Estimation	CodeCode Available	1
Unsupervised object-centric video generation and decomposition in 3D	Jul 7, 2020	3D Object DetectionDepth Estimation	CodeCode Available	0
Wasserstein Distances for Stereo Disparity Estimation	Jul 6, 2020	3D Object Detection3D Object Detection From Stereo Images	CodeCode Available	1
Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy	Jul 5, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
Synergistic saliency and depth prediction for RGB-D saliency detection	Jul 3, 2020	Depth EstimationDepth Prediction	—Unverified	0
Data-Driven Method for Enhanced Corrosion Assessment of Reinforced Concrete Structures	Jul 1, 2020	Depth EstimationDepth Prediction	—Unverified	0
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner	Jun 30, 2020	BenchmarkingDepth Estimation	CodeCode Available	1
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion	Jun 28, 2020	3D ReconstructionDepth Estimation	—Unverified	0
MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation	Jun 27, 2020	CPUDepth Estimation	—Unverified	0
MTStereo 2.0: improved accuracy of stereo depth estimation withMax-trees	Jun 27, 2020	Depth EstimationGPU	CodeCode Available	1
An Advert Creation System for 3D Product Placements	Jun 26, 2020	3D geometryDepth Estimation	—Unverified	0
Increased-Range Unsupervised Monocular Depth Estimation	Jun 23, 2020	Depth EstimationGPU	—Unverified	0
Regression Prior Networks	Jun 20, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Self-Supervised Joint Learning Framework of Depth Estimation via Implicit Cues	Jun 17, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
AcED: Accurate and Edge-consistent Monocular Depth Estimation	Jun 16, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
Depth by Poking: Learning to Estimate Depth from Self-Supervised Grasping	Jun 16, 2020	Depth EstimationPosition	—Unverified	0
Targeted Adversarial Perturbations for Monocular Depth Prediction	Jun 12, 2020	Adversarial AttackAdversarial Defense	CodeCode Available	1
Attentive Feature Reuse for Multi Task Meta learning	Jun 12, 2020	Depth EstimationGeneral Classification	—Unverified	0
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies	Jun 10, 2020	3D Object DetectionAutonomous Driving	—Unverified	0

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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