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 1901–1925 of 2454 papers

Title	Date	Tasks	Status	Hype
Real-time single image depth perception in the wild with handheld devices	Jun 10, 2020	Autonomous DrivingDepth Estimation	CodeCode Available	1
Semantics-Driven Unsupervised Learning for Monocular Depth and Ego-Motion Estimation	Jun 8, 2020	Depth EstimationDepth Prediction	—Unverified	0
SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation	Jun 7, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction	Jun 7, 2020	Depth EstimationDepth Prediction	—Unverified	0
Robust Learning Through Cross-Task Consistency	Jun 7, 2020	3D ReconstructionDepth Estimation	CodeCode Available	1
FP-Stereo: Hardware-Efficient Stereo Vision for Embedded Applications	Jun 5, 2020	C++ codeDepth Estimation	—Unverified	0
Content-Aware Inter-Scale Cost Aggregation for Stereo Matching	Jun 5, 2020	Depth EstimationStereo Matching	—Unverified	0
Auto-Rectify Network for Unsupervised Indoor Depth Estimation	Jun 4, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
From Real to Synthetic and Back: Synthesizing Training Data for Multi-Person Scene Understanding	Jun 3, 2020	Depth EstimationGenerative Adversarial Network	—Unverified	0
PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation	Jun 3, 2020	Depth EstimationMonocular Depth Estimation	—Unverified	0
IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous Driving	Jun 1, 2020	3D Object DetectionAutonomous Driving	CodeCode Available	1
Height and Uprightness Invariance for 3D Prediction From a Single View	Jun 1, 2020	Camera Pose EstimationDepth Estimation	CodeCode Available	1
Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery	Jun 1, 2020	counterfactualDepth Estimation	—Unverified	0
Disparity-Aware Domain Adaptation in Stereo Image Restoration	Jun 1, 2020	Depth EstimationDisparity Estimation	—Unverified	0
Online Depth Learning Against Forgetting in Monocular Videos	Jun 1, 2020	Depth EstimationMeta-Learning	—Unverified	0
Pattern-Structure Diffusion for Multi-Task Learning	Jun 1, 2020	Depth EstimationMulti-Task Learning	—Unverified	0
Robust Learning Through Cross-Task Consistency	Jun 1, 2020	3D ReconstructionDepth Estimation	CodeCode Available	1
SDC-Depth: Semantic Divide-and-Conquer Network for Monocular Depth Estimation	Jun 1, 2020	DecoderDepth Estimation	—Unverified	0
BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion	Jun 1, 2020	Depth Estimation	CodeCode Available	1
Structure-Guided Ranking Loss for Single Image Depth Prediction	Jun 1, 2020	Depth EstimationDepth Prediction	CodeCode Available	1
Attention-Aware Multi-View Stereo	Jun 1, 2020	Depth Estimation	—Unverified	0
A Survey on Deep Learning Techniques for Stereo-based Depth Estimation	Jun 1, 2020	Autonomous DrivingDeep Learning	—Unverified	0
Upgrading Optical Flow to 3D Scene Flow Through Optical Expansion	Jun 1, 2020	Depth EstimationOptical Flow Estimation	CodeCode Available	1
VPLNet: Deep Single View Normal Estimation With Vanishing Points and Lines	Jun 1, 2020	Depth EstimationSurface Normal Estimation	—Unverified	0
Why Having 10,000 Parameters in Your Camera Model Is Better Than Twelve	Jun 1, 2020	Camera CalibrationCamera Pose 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