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 2351–2375 of 2454 papers

Title	Date	Tasks	Status	Hype
Multi-task Self-Supervised Visual Learning	Aug 25, 2017	Depth EstimationDepth Prediction	—Unverified	0
Sparsity Invariant CNNs	Aug 22, 2017	Depth CompletionDepth Estimation	CodeCode Available	0
Reflection Separation and Deblurring of Plenoptic Images	Aug 22, 2017	DeblurringDepth Estimation	—Unverified	0
Learning to Synthesize a 4D RGBD Light Field from a Single Image	Aug 10, 2017	Depth Estimation	CodeCode Available	0
SPLODE: Semi-Probabilistic Point and Line Odometry with Depth Estimation from RGB-D Camera Motion	Aug 9, 2017	Depth EstimationMotion Estimation	—Unverified	0
Fast Scene Understanding for Autonomous Driving	Aug 8, 2017	Autonomous DrivingDecoder	CodeCode Available	0
Accurate Light Field Depth Estimation with Superpixel Regularization over Partially Occluded Regions	Aug 7, 2017	Depth Estimation	—Unverified	0
Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum Inference	Aug 2, 2017	Depth EstimationMonocular Depth Estimation	CodeCode Available	0
Occlusion Handling using Semantic Segmentation and Visibility-Based Rendering for Mixed Reality	Jul 30, 2017	Depth EstimationMixed Reality	—Unverified	0
The Devil is in the Decoder: Classification, Regression and GANs	Jul 18, 2017	Boundary DetectionDecoder	CodeCode Available	0
Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks	Jul 4, 2017	Depth Estimation	—Unverified	0
A Wide-Field-Of-View Monocentric Light Field Camera	Jul 1, 2017	Depth Estimation	—Unverified	0
Recurrent Scene Parsing with Perspective Understanding in the Loop	May 20, 2017	Depth EstimationMonocular Depth Estimation	CodeCode Available	0
Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery	May 17, 2017	Depth EstimationDepth Prediction	—Unverified	0
Out-of-focus: Learning Depth from Image Bokeh for Robotic Perception	May 2, 2017	Depth Estimation	—Unverified	0
Single image depth estimation by dilated deep residual convolutional neural network and soft-weight-sum inference	Apr 27, 2017	Depth Estimation	CodeCode Available	0
Unsupervised Learning of Depth and Ego-Motion from Video	Apr 25, 2017	Camera Pose EstimationDepth And Camera Motion	CodeCode Available	0
OCRAPOSE II: An OCR-based indoor positioning system using mobile phone images	Apr 19, 2017	Depth EstimationOptical Character Recognition	—Unverified	0
CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction	Apr 11, 2017	Depth EstimationDepth Prediction	CodeCode Available	0
Surface Normals in the Wild	Apr 10, 2017	Depth Estimation	—Unverified	0
Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation	Apr 7, 2017	Depth EstimationMonocular Depth Estimation	CodeCode Available	0
Deep Depth From Focus	Apr 4, 2017	Depth Estimation	CodeCode Available	1
SeGAN: Segmenting and Generating the Invisible	Mar 29, 2017	Depth EstimationScene Understanding	CodeCode Available	0
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?	Mar 15, 2017	Deep LearningDepth Estimation	CodeCode Available	1
Depth from Monocular Images using a Semi-Parallel Deep Neural Network (SPDNN) Hybrid Architecture	Mar 10, 2017	Depth EstimationStereo Depth 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