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 901–925 of 2454 papers

Title	Date	Tasks	Status	Score
Consensus-based Optimization for 3D Human Pose Estimation in Camera Coordinates	Nov 21, 2019	3D Human Pose EstimationDepth Estimation	CodeCode Available	5
MVDepthNet: Real-time Multiview Depth Estimation Neural Network	Jul 23, 2018	Data AugmentationDecoder	CodeCode Available	5
Achieving Risk Control in Online Learning Settings	May 18, 2022	Conformal PredictionDepth Estimation	CodeCode Available	5
DPF^*: improved Depth Potential Function for scale-invariant sulcal depth estimation	Jan 9, 2025	Depth Estimation	CodeCode Available	5
Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map Prediction	Jul 23, 2019	Autonomous DrivingDepth Completion	CodeCode Available	5
MonoSIM: Simulating Learning Behaviors of Heterogeneous Point Cloud Object Detectors for Monocular 3D Object Detection	Aug 19, 2022	3D Object DetectionAutonomous Driving	CodeCode Available	5
A step towards understanding why classification helps regression	Aug 21, 2023	Age EstimationClassification	CodeCode Available	5
A Simple Framework for 3D Lensless Imaging with Programmable Masks	Aug 18, 2021	Depth Estimation	CodeCode Available	5
On the Viability of Monocular Depth Pre-training for Semantic Segmentation	Mar 26, 2022	Depth EstimationDepth Prediction	CodeCode Available	5
Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum Inference	Aug 2, 2017	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Monocular Depth Parameterizing Networks	Dec 21, 2020	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization	Nov 26, 2018	2D Object Detection3D Object Detection	CodeCode Available	5
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation	Nov 5, 2020	Depth Estimation	CodeCode Available	5
Monocular Depth Decomposition of Semi-Transparent Volume Renderings	Jun 27, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Monocular Depth Estimation Using Cues Inspired by Biological Vision Systems	Apr 21, 2022	Depth EstimationDepth Prediction	CodeCode Available	5
D-Net: A Generalised and Optimised Deep Network for Monocular Depth Estimation	Sep 29, 2021	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation	May 24, 2018	Depth EstimationDepth Prediction	CodeCode Available	5
Sparse and noisy LiDAR completion with RGB guidance and uncertainty	Feb 14, 2019	Autonomous VehiclesDepth Completion	CodeCode Available	5
Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud	Mar 23, 2019	3D Object DetectionDepth Estimation	CodeCode Available	5
Color-Guided Flying Pixel Correction in Depth Images	Oct 10, 2024	Depth Estimation	CodeCode Available	5
Generating and Exploiting Probabilistic Monocular Depth Estimates	Jun 13, 2019	Depth CompletionDepth Estimation	CodeCode Available	5
Deep Vision-Based Framework for Coastal Flood Prediction Under Climate Change Impacts and Shoreline Adaptations	Jun 6, 2024	Depth EstimationFlood Inundation Mapping	CodeCode Available	5
Monocular Depth Estimation using Multi-Scale Continuous CRFs as Sequential Deep Networks	Mar 1, 2018	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers	Feb 3, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
METER: a mobile vision transformer architecture for monocular depth estimation	Mar 13, 2024	CPUData Augmentation	CodeCode Available	5

Show:10 25 50

← PrevPage 37 of 99Next →

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