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 1801–1825 of 2454 papers

Title	Date	Tasks	Status	Hype
MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene Flow	Oct 21, 2020	Depth EstimationOptical Flow Estimation	—Unverified	0
Distortion-aware Monocular Depth Estimation for Omnidirectional Images	Oct 18, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
What Can You Learn from Your Muscles? Learning Visual Representation from Human Interactions	Oct 16, 2020	Action RecognitionDepth Estimation	CodeCode Available	1
Learning Monocular Dense Depth from Events	Oct 16, 2020	Depth EstimationDepth Prediction	CodeCode Available	1
Relative Depth Estimation as a Ranking Problem	Oct 14, 2020	Depth Estimation	—Unverified	0
A New Distributional Ranking Loss With Uncertainty: Illustrated in Relative Depth Estimation	Oct 14, 2020	Depth Estimation	—Unverified	0
Unsupervised Learning of Depth and Ego-Motion from Cylindrical Panoramic Video with Applications for Virtual Reality	Oct 14, 2020	Depth EstimationMotion Estimation	CodeCode Available	1
Spatially-Variant CNN-based Point Spread Function Estimation for Blind Deconvolution and Depth Estimation in Optical Microscopy	Oct 8, 2020	Depth Estimation	CodeCode Available	1
Parallax Motion Effect Generation Through Instance Segmentation And Depth Estimation	Oct 6, 2020	Depth EstimationInstance Segmentation	—Unverified	0
Adversarial Patch Attacks on Monocular Depth Estimation Networks	Oct 6, 2020	Adversarial AttackDepth Estimation	—Unverified	0
SAFENet: Self-Supervised Monocular Depth Estimation with Semantic-Aware Feature Extraction	Oct 6, 2020	Depth EstimationDepth Prediction	CodeCode Available	0
Joint Pruning & Quantization for Extremely Sparse Neural Networks	Oct 5, 2020	Depth EstimationQuantization	—Unverified	0
Unsupervised Monocular Depth Estimation for Night-time Images using Adversarial Domain Feature Adaptation	Oct 3, 2020	DecoderDepth Estimation	CodeCode Available	1
Monocular Differentiable Rendering for Self-Supervised 3D Object Detection	Sep 30, 2020	3D Object Detection3D Object Detection From Monocular Images	—Unverified	0
Light Field Compression by Residual CNN Assisted JPEG	Sep 30, 2020	Depth EstimationSSIM	CodeCode Available	0
Depth Estimation from Monocular Images and Sparse Radar Data	Sep 30, 2020	Depth Estimation	CodeCode Available	1
Adaptive confidence thresholding for monocular depth estimation	Sep 27, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Towards General Purpose Geometry-Preserving Single-View Depth Estimation	Sep 25, 2020	Depth EstimationDiversity	—Unverified	0
Calibrating Self-supervised Monocular Depth Estimation	Sep 16, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
Cascade Network for Self-Supervised Monocular Depth Estimation	Sep 14, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
Monocular Depth Estimation Using Multi Scale Neural Network And Feature Fusion	Sep 11, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
Adjusting Bias in Long Range Stereo Matching: A semantics guided approach	Sep 10, 2020	3D Object DetectionAutonomous Navigation	—Unverified	0
View-consistent 4D Light Field Depth Estimation	Sep 9, 2020	Depth Estimation	CodeCode Available	1
Rain rendering for evaluating and improving robustness to bad weather	Sep 6, 2020	Depth EstimationObject	—Unverified	0
Approaches, Challenges, and Applications for Deep Visual Odometry: Toward to Complicated and Emerging Areas	Sep 6, 2020	Deep LearningDepth Estimation	—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