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< Last updated: 15/12/2023 >
| Dataset Name | Year | Publication | Links |
|---|---|---|---|
| Multi-Spectral Stereo Outdoor Driving Dataset | 2023 | CVPR | Paper |
| Year | Model & Method | Publication | Title | Links |
|---|---|---|---|---|
| 2023 | Transformer, Cross-attention | IEEE Transactions on Pattern Analysis and Machine Intelligence | Unifying Flow, Stereo and Depth Estimation | Paper/Code |
| 2023 | md4all | ICCV | Robust Monocular Depth Estimation under Challenging Conditions | Paper/Code |
| 2023 | - | WACV | The Monocular Depth Estimation Challenge | Paper/Code |
| 2023 | - | WACV | The Second Monocular Depth Estimation Challenge | Paper/Code |
| 2023 | Physics (geometry)-driven deep learning framework | ICCV | NDDepth: Normal-Distance Assisted Monocular Depth Estimation | Paper/Code |
| 2023 | A parallel encoder architecture consisting of a Transformer branch and a convolution branch | Machine Intelligence Research | DepthFormer: Exploiting Long-range Correlation and Local Information for Accurate Monocular Depth Estimation | Paper/Code |
| 2023 | An effective method for creating temporal stereo by dynamically determining the center and range of the temporal stereo | AAAI | BEVStereo: Enhancing Depth Estimation in Multi-View 3D Object Detection with Temporal Stereo | Paper/Code |
| 2023 | CNNs, Transformers, and CNN-Transformer hybrid models | AAAI | Deep Digging into the Generalization of Self-Supervised Monocular Depth Estimation | Paper/Code |
| 2023 | HRDFuse(CNNs + transformers) | CVPR | HRDFuse: Monocular 360deg Depth Estimation by Collaboratively Learning Holistic-With-Regional Depth Distributions | Paper/Code |
| 2023 | Diffusion Models | arXiv | Monocular Depth Estimation using Diffusion Models | Paper/Code |
| 2023 | Cross-view self-attention | PMLR | SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation | Paper/Code |
| 2023 | Internal Discretization (ID) | CVPR | iDisc: Internal Discretization for Monocular Depth Estimation | Paper/Code |
| 2023 | Consistent Online Dynamic Depth (CODD) | WACV | Temporally Consistent Online Depth Estimation in Dynamic Scenes | Paper/Code |
| 2023 | DPS-Net | ICCV | DPS-Net: Deep Polarimetric Stereo Depth Estimation | Paper/Code |
| 2023 | Two-View Pose Estimator | CVPR | LightedDepth: Video Depth Estimation in Light of Limited Inference View Angles | Paper/Code |
| 2023 | SABV-Depth (based on the self-attention mechanism) | Knowledge-Based Systems | SABV-Depth: A biologically inspired deep learning network for monocular depth estimation | Paper/Code |
| 2023 | SC-DepthV3 | IEEE Transactions on Pattern Analysis and Machine Intelligence | SC-DepthV3: Robust Self-Supervised Monocular Depth Estimation for Dynamic Scenes | Paper/Code |
| 2023 | Pseudo-supervised loss | ICCV | Self-supervised Monocular Depth Estimation: Let's Talk About The Weather | Paper/Code |
| 2023 | Fit a neural RGB-D representation to long-burst data and simultaneously estimates scene depth and camera motion | CVPR | Shakes on a Plane: Unsupervised Depth Estimation From Unstabilized Photography | Paper/Code |
| 2023 | Exploit GCN for a self-supervised monocular depth estimation model | Neurocomputing | GCNDepth: Self-supervised monocular depth estimation based on graph convolutional network | Paper/Code |
| 2023 | Gated fusion scheme | CVPR | Depth Estimation From Camera Image and mmWave Radar Point Cloud | Paper/Code |
| 2023 | DPT algorithm | CVPR | High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation | Paper/Code |
| 2023 | knowledge distillation (KD) | International Conference on Knowledge Science, Engineering and Management | Boosting LightWeight Depth Estimation via Knowledge Distillation | Paper/Code |
| 2023 | Domain adaptation approach | International Journal of Computer Vision | DESC: Domain Adaptation for Depth Estimation via Semantic Consistency | Paper/Code |
| 2023 | CNN | ISPRS Journal of Photogrammetry and Remote Sensing | Snow depth estimation at country-scale with high spatial and temporal resolution | Paper/Code |
| 2023 | Consider the task of depth estimation as a ranking problem, i.e., for a given pair of points, we estimate which point is nearer to the camera | CVPR | Analyzing Results of Depth Estimation Models With Monocular Criteria | Paper/Code |
| 2023 | 360MonoDepth | CVPR | High-Resolution Depth Estimation for 360deg Panoramas Through Perspective and Panoramic Depth Images Registration | Paper/Code |
| 2023 | Propose a learning framework that trains models to predict geometry-preserving depth without requiring extra data or annotations | ICCV | Robust Geometry-Preserving Depth Estimation Using Differentiable Rendering | Paper/Code |
| 2023 | Combination of CNNs and Transformers | CVPR | Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation | Paper/Code |
| 2023 | EPNet | AAAI | Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation | Paper/Code |
| 2023 | A novel memory and attention framework | ICCV | MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation | Paper/Code |
| 2023 | UDepth (MobileNetV2, Transformer-based optimizer) | ICRA | UDepth: Fast Monocular Depth Estimation for Visually-guided Underwater Robots | Paper/Code |
| 2023 | CNN | Computers and Electronics in Agriculture | Accurate detection and depth estimation of table grapes and peduncles for robot harvesting, combining monocular depth estimation and CNN methods | Paper/Code |
| 2023 | Propose an initialization method for the network weights based on the Manhattan World Assumption | CVPR | Depth Estimation From Indoor Panoramas With Neural Scene Representation | Paper/Code |
| 2023 | Propose to detect OOD images from an encoder-decoder depth estimation model based on the reconstruction error | ICCV | Out-of-Distribution Detection for Monocular Depth Estimation | Paper/Code |
| 2023 | Propose a novel approach that utilizes both local and global features in the cost volume for depth estimation | CVPR | Disentangling Local and Global Information for Light Field Depth Estimation | Paper/Code |
| 2023 | Self-reprojection mask, self-statistical mask, self-distillation augmentation | IEEE Transactions on Neural Networks and Learning Systems | Self-Supervised Monocular Depth Estimation With Self-Perceptual Anomaly Handling | Paper/Code |
| 2023 | A two-stage attention-based occlusion-aware light field depth estimation network | Optics and Lasers in Engineering | Occlusion-aware light field depth estimation with view attention | Paper/Code |
| 2023 | Estimate temporally consistent depth maps of video streams in an online setting | CVPR | Temporally Consistent Online Depth Estimation Using Point-Based Fusion | Paper/Code |
| 2023 | EPI, multi-view depth integration strategy | Pattern Recognition | Accurate light field depth estimation under occlusion | Paper/Code |
| 2023 | RoboDepth | arXiv | RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions | Paper/Code |
| 2023 | Ground attention | ICCV | GEDepth: Ground Embedding for Monocular Depth Estimation | Paper/Code |
| 2023 | Self-supervised deep learning, joint depth and ego-motion estimation | PMLR | When the Sun Goes Down: Repairing Photometric Losses for All-Day Depth Estimation | Paper/Code |
| 2023 | Redesign the patch-based triplet loss in MDE | WACV | Self-Supervised Monocular Depth Estimation: Solving the Edge-Fattening Problem | Paper/Code |
| 2023 | - | CVPR | LFNAT 2023 Challenge on Light Field Depth Estimation: Methods and Results | Paper/Code |
| 2023 | Self-supervised depth estimation with semantics | Pattern Recognition | Learning depth via leveraging semantics: Self-supervised monocular depth estimation with both implicit and explicit semantic guidance | Paper/Code |
| 2023 | CNN-LSTM | NDT & E International | Automatic defect depth estimation for ultrasonic testing in carbon fiber reinforced composites using deep learning | Paper/Code |
| 2023 | Transformer | ICRA | TODE-Trans: Transparent Object Depth Estimation with Transformer | Paper/Code |
| 2023 | Semi-supervised, domain-adaptive semantic segmentation | International Journal of Computer Vision | Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation | Paper/Code |
| 2023 | Summarize the LF depth estimation methods | High-Confidence Computing | Light field depth estimation: A comprehensive survey from principles to future | Paper/Code |
| 2023 | Densely estimating metric depth | Computer Vision and Image Understanding | LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR | Paper/Code |
| 2023 | Multi-head attention (MHA) modules | CVPR | Trap Attention: Monocular Depth Estimation With Manual Traps | Paper/Code |
| 2023 | CSMHNet (a hybrid of a Convolution, self-attention, and an MLP network) | Engineering Applications of Artificial Intelligence | Self-supervised monocular depth estimation based on combining convolution and multilayer perceptron | Paper/Code |
| 2023 | Direction-aware Cumulative Convolution Network (DaCCN) | CVPR | Self-Supervised Monocular Depth Estimation by Direction-aware Cumulative Convolution Network | Paper/Code |
| 2023 | - | IPOL Journal · Image Processing On Line | Monocular Depth Estimation: a Review of the 2022 State of the Art | Paper/Code |
| 2023 | Two-in-One self-supervised depth estimation network, called TiO-Depth | ICCV | Two-in-One Depth: Bridging the Gap Between Monocular and Binocular Self-Supervised Depth Estimation | Paper/Code |
| 2023 | PlaneDepth (Laplacian Mixture Model based on orthogonal planes for an input image) | CVPR | PlaneDepth: Self-Supervised Depth Estimation via Orthogonal Planes | Paper/Code |
| 2023 | CNNs (ResNet50) | Expert Systems with Applications | Analyzing CARLA ’s performance for 2D object detection and monocular depth estimation based on deep learning approaches | Paper/Code |
| 2023 | Uncertain pixel masking strategy | arXiv | STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth Estimation | Paper/Code |
| 2023 | Two-headed Depth Estimation and Deblurring Network (2HDED:NET) | IEEE Transactions on Computational Imaging | Depth Estimation and Image Restoration by Deep Learning From Defocused Images | Paper/Code |
| 2023 | Transformer, CNNs | ISMAR | MonoVAN: Visual Attention for Self-Supervised Monocular Depth Estimation | Paper/Code |
| 2023 | CNNs, MLP | The Journal of Supercomputing | Car depth estimation within a monocular image using a light CNN | Paper/Code |
| 2023 | Self-supervised framework | CVPR | Fully Self-Supervised Depth Estimation From Defocus Clue | Paper/Code |
| 2023 | Attention | CVPR | EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation | Paper/Code |
| 2023 | Binocular depth estimation network | CVPR | OmniVidar: Omnidirectional Depth Estimation From Multi-Fisheye Images | Paper/Code |
| 2023 | Self-supervised learning, feature-level adversarial adaptation | WACV | Self-Supervised Monocular Depth Estimation From Thermal Images via Adversarial Multi-Spectral Adaptation | Paper/Code |
| Year | Model & Method | Publication | Title | Links |
|---|---|---|---|---|
| 2023 | Gradient loss | Engineering Applications of Artificial Intelligence | A geometry-aware deep network for depth estimation in monocular endoscopy | Paper/Code |
| 2023 | SLAM | Computers in Biology and Medicine | Sparse-to-dense coarse-to-fine depth estimation for colonoscopy | Paper/Code |
| 2023 | Active inference | MDPI | Active Vision in Binocular Depth Estimation: A Top-Down Perspective | Paper/Code |
| 2023 | Spatiotemporal vision transformers-based self-supervised depth estimation | IEEE Transactions on Medical Robotics and Bionics | SVT-SDE: Spatiotemporal Vision Transformers-Based Self-Supervised Depth Estimation in Stereoscopic Surgical Videos | Paper/Code |
| 2023 | Combine both supervised and self-supervised loss | Intelligent Medicine | ArthroNet: a monocular depth estimation technique with 3D segmented maps for knee arthroscopy | Paper/Code |
| 2023 | U-shape convolutional network with the dual-attention mechanism | Computer Methods and Programs in Biomedicine | Self-supervised monocular depth estimation for gastrointestinal endoscopy | Paper/Code |
| 2023 | Triple-supervision learning framework | ICASSP | Deep Triple-Supervision Learning Unannotated Surgical Endoscopic Video Data for Monocular Dense Depth Estimation | Paper/Code |
| 2023 | Pixel-level depth map fusion algorithm | IEEE International Conference on Image Processing | Dense Depth Estimation for Surgical Endoscope Robot with Multi-Baseline Depth Map Fusion | Paper/Code |
| 2023 | NeRF, SLAM | MLMI | Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos Using NeRFs | Paper/Code |
| 2023 | Self-supervised depth and ego-motion estimation system | arXiv | WS-SfMLearner: Self-supervised Monocular Depth and Ego-motion Estimation on Surgical Videos with Unknown Camera Parameters | Paper/Code |
| 2023 | Semantic-SuPer, that integrates geometric and semantic information to facilitate data association, 3D reconstruction, and tracking of endoscopic scenes, benefiting downstream tasks like surgical navigation | ICRA | Semantic-SuPer: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Identification, Reconstruction, and Tracking | Paper/Code |
| 2023 | Second-order gradient of the image, second-order gradient of the parallax map | ICCECE | Monocular depth estimation based on Chained Residual Pooling and Gradient Weighted Loss | Paper/Code |
| 2023 | Self-supervised depth estimation | arXiv | SemHint-MD: Learning from Noisy Semantic Labels for Self-Supervised Monocular Depth Estimation | Paper/Code |
| 2023 | Regression network | MICCAI | Detecting the Sensing Area of a Laparoscopic Probe in Minimally Invasive Cancer Surgery | Paper/Code |
| 2023 | - | Journal of Physics: Conference Series | A survey on deep learning for surgical planning | Paper/Code |
| 2023 | cGAN-based network Bronchoscopic-Depth-GAN (BronchoDep-GAN) | International Journal of Computer Assisted Radiology and Surgery | A cGAN-based network for depth estimation from bronchoscopic images | Paper/Code |
| 2023 | NeFR | Predictive Intelligence in Medicine | Dynamic Depth-Supervised NeRF for Multi-view RGB-D Operating Room Videos | Paper/Code |