SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth Estimation | ✓ Link | 0.071 | 3.662 | 0.153 | 0.531 | 0.94 | 0.973 | 0.985 | 1024x320 | X | 1 | SPIdepth | 2024-04-18 |
PlaneDepth: Self-supervised Depth Estimation via Orthogonal Planes | ✓ Link | 0.084 | 3.981 | 0.169 | 0.549 | 0.911 | 0.968 | 0.984 | 1280x384 | X | | PlaneDepth (S + 1280x384) | 2022-10-04 |
ProDepth: Boosting Self-Supervised Multi-Frame Monocular Depth with Probabilistic Fusion | ✓ Link | 0.086 | 4.139 | 0.166 | 0.629 | 0.918 | 0.969 | 0.984 | 640x192 | O | 2(-1,0) | ProDepth | 2024-07-12 |
Jasmine: Harnessing Diffusion Prior for Self-supervised Depth Estimation | | 0.09 | 3.944 | 0.161 | 0.581 | 0.919 | 0.972 | 0.986 | 1024x320 | O | | Jasmine | 2025-03-20 |
SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint Learning | ✓ Link | 0.090 | 4.056 | 0.166 | 0.650 | 0.918 | 0.970 | 0.985 | 640x192 | | | SCIPaD | 2024-07-07 |
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation | | 0.090 | 4.113 | 0.167 | 0.655 | 0.914 | 0.969 | 0.985 | | O | | DCPI-Depth (M+1024x320) | 2024-05-27 |
Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation | ✓ Link | 0.091 | 4.207 | 0.176 | 0.646 | 0.901 | 0.966 | 0.983 | 1024x320 | X | | EPCDepth(S+1024x320) | 2021-09-26 |
Manydepth2: Motion-Aware Self-Supervised Multi-Frame Monocular Depth Estimation in Dynamic Scenes | ✓ Link | 0.091 | 4.232 | 0.170 | 0.649 | 0.909 | 0.968 | 0.984 | 640x192 | O | | Manydepth2(M+640x192) | 2023-12-23 |
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training | ✓ Link | 0.092 | 4.194 | 0.165 | 0.646 | 0.910 | 0.970 | 0.986 | 640x192 | O | | NimbleD-LiteMono-8M | 2024-08-26 |
MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer | ✓ Link | 0.093 | 4.202 | 0.169 | 0.671 | 0.912 | 0.969 | 0.985 | 1024x320 | X | | MonoViT(MS+1024x320) | 2022-08-06 |
Manydepth2: Motion-Aware Self-Supervised Multi-Frame Monocular Depth Estimation in Dynamic Scenes | ✓ Link | 0.094 | 4.246 | 0.170 | 0.676 | 0.909 | 0.968 | 0.985 | 640x192 | O | | Manydepth2-NF(M+640x192) | 2023-12-23 |
Self-Supervised Monocular Depth Estimation with Internal Feature Fusion | ✓ Link | 0.094 | 4.250 | 0.172 | 0.678 | 0.911 | 0.968 | 0.984 | | X | | DIFFNet (MS+1024x320) | 2021-10-18 |
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation | | 0.095 | 4.274 | 0.170 | 0.662 | 0.902 | 0.967 | 0.985 | | | | DCPI-Depth (M+640x192) | 2024-05-27 |
TransDSSL: Transformer based Depth Estimation via Self-Supervised Learning | ✓ Link | 0.095 | 4.321 | 0.172 | 0.711 | 0.906 | 0.967 | 0.984 | | O | | TransDSSL | 2022-08-05 |
DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost Volume | ✓ Link | 0.095 | 4.329 | 0.173 | 0.698 | 0.905 | 0.966 | 0.984 | | | | DS-Depth | 2023-08-14 |
ProDepth: Boosting Self-Supervised Multi-Frame Monocular Depth with Probabilistic Fusion | ✓ Link | 0.095 | 4.345 | 0.172 | 0.693 | 0.902 | 0.967 | 0.985 | 640x192 | O | | ProDepth(M+640x192) | 2024-07-12 |
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation | ✓ Link | 0.096 | 4.264 | 0.173 | 0.694 | | | | | | | CADepth-Net (MS+1024x320) | 2021-12-24 |
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training | ✓ Link | 0.096 | 4.304 | 0.171 | 0.684 | 0.903 | 0.969 | 0.986 | 640x192 | O | | NimbleD-LiteMono | 2024-08-26 |
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training | ✓ Link | 0.096 | 4.333 | 0.171 | 0.697 | 0.905 | 0.969 | 0.986 | 640x192 | O | | Nimbled-SwiftDepth | 2024-08-26 |
Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth | ✓ Link | 0.096 | 4.458 | 0.175 | 0.720 | 0.897 | 0.964 | 0.984 | | X | | DynamicDepth (M+640x192) | 2022-03-29 |
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training | ✓ Link | 0.097 | 4.377 | 0.172 | 0.721 | 0.904 | 0.968 | 0.985 | 640x192 | O | | Nimbled-MD2-R50 | 2024-08-26 |
SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint Learning | ✓ Link | 0.098 | 4.391 | 0.175 | 0.732 | 0.897 | 0.964 | 0.983 | 640x192 | O | | SCIPaD(M+640x192) | 2024-07-07 |
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training | ✓ Link | 0.098 | 4.401 | 0.174 | 0.733 | 0.901 | 0.968 | 0.985 | 640x192 | O | | Nimbled-SwiftDepth-S | 2024-08-26 |
Towards Comprehensive Representation Enhancement in Semantics-guided Self-supervised Monocular Depth Estimation | | 0.099 | 4.165 | 0.171 | 0.624 | 0.902 | 0.969 | 0.986 | | | | CREMono(M + 1024x320 + Res50) | 2022-10-23 |
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training | ✓ Link | 0.099 | 4.370 | 0.172 | 0.709 | 0.898 | 0.967 | 0.986 | 640x192 | O | | NimbleD-LiteMono-S | 2024-08-26 |
Feature-metric Loss for Self-supervised Learning of Depth and Egomotion | ✓ Link | 0.099 | 4.427 | 0.184 | 0.697 | 0.889 | 0.963 | 0.982 | | | | FeatDepth-MS | 2020-07-21 |
Exploring Efficiency of Vision Transformers for Self-Supervised Monocular Depth Estimation | ✓ Link | 0.099 | 4.439 | 0.178 | 0.743 | 0.904 | 0.965 | 0.983 | | | | VTDepthB2 (stereo supervision) | 2022-12-27 |
Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation | ✓ Link | 0.099 | 4.490 | 0.183 | 0.754 | 0.888 | 0.963 | 0.982 | | | | EPCDepth(S+640x192) | 2021-09-26 |
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training | ✓ Link | 0.100 | 4.440 | 0.175 | 0.739 | 0.898 | 0.967 | 0.985 | 640x192 | O | | Nimbled-MD2-R18 | 2024-08-26 |
Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervision | ✓ Link | 0.101 | 4.413 | | 0.703 | 0.882 | 0.962 | | | | | MonoDEVSNet | 2021-03-22 |
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation | ✓ Link | 0.101 | | | | | | | | | | HR-Depth-MS-1024X320 | 2020-12-14 |
X-Distill: Improving Self-Supervised Monocular Depth via Cross-Task Distillation | | 0.102 | 4.439 | 0.180 | 0.698 | 0.895 | 0.965 | 0.983 | | | | X-Distill (M+1024x320) | 2021-10-24 |
CamLessMonoDepth: Monocular Depth Estimation with Unknown Camera Parameters | | 0.102 | | | | | | | | | | CamLessMonoDepth-1024x320 | 2021-10-27 |
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional Network | ✓ Link | 0.104 | 4.494 | 0.181 | 0.720 | | | | | | | GCNDepth | 2021-12-13 |
Feature-metric Loss for Self-supervised Learning of Depth and Egomotion | ✓ Link | 0.104 | | | | | | | | | | FeatDepth-M | 2020-07-21 |
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation | ✓ Link | 0.104 | | | | | | | | | | HR-Depth-M-1280x384 | 2020-12-14 |
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation | ✓ Link | 0.104 | | | | | | | | | | Lite-HR-Depth-T-1280x384 | 2020-12-14 |
Deep Digging into the Generalization of Self-Supervised Monocular Depth Estimation | ✓ Link | 0.104 | | | | | | | 640x192 | O | | MonoFormer | 2022-05-23 |
Exploring Efficiency of Vision Transformers for Self-Supervised Monocular Depth Estimation | ✓ Link | 0.105 | 4.530 | 0.182 | 0.762 | 0.893 | 0.964 | 0.983 | | | | VTDepthB2 (monocular supervision) | 2022-12-27 |
CamLessMonoDepth: Monocular Depth Estimation with Unknown Camera Parameters | | 0.105 | | | | | | | | | | CamLessMonoDepth (V1)-640x192 | 2021-10-27 |
Digging Into Self-Supervised Monocular Depth Estimation | ✓ Link | 0.106 | | | | | | | | | | Monodepth2 MS | 2019-10-01 |
CamLessMonoDepth: Monocular Depth Estimation with Unknown Camera Parameters | | 0.106 | | | | | | | | | | CamLessMonoDepth (V2)-640x192 | 2021-10-27 |
3D Packing for Self-Supervised Monocular Depth Estimation | ✓ Link | 0.107 | | | | | | | | | | PackNet-SfM M | 2019-05-06 |
SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation | ✓ Link | 0.109 | 3.77 | 0.19 | 0.673 | 0.864 | 0.954 | 0.981 | | | | SharinGAN | 2020-06-07 |
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation | | 0.109 | 4.496 | | 0.679 | | | | | | | DCPI-Depth (M+832x256+SC-V3) | 2024-05-27 |
Digging Into Self-Supervised Monocular Depth Estimation | ✓ Link | 0.109 | | | | | | | | | | Monodepth2 S | 2019-10-01 |
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation | ✓ Link | 0.109 | | | | | | | | | | HR-Depth-M-640x192 | 2020-12-14 |
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation | ✓ Link | 0.109 | | | | | | | | | | G2S (MD2-M-R18-pp-640 x 192) | 2021-03-03 |
SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation | | 0.112 | | | | | | | | | | SuperDepth S | 2018-10-03 |
Improving Self-Supervised Single View Depth Estimation by Masking Occlusion | ✓ Link | 0.113 | | | | | | | | | | Occlusion_mask_640x192 | 2019-08-29 |
Pose Constraints for Consistent Self-supervised Monocular Depth and Ego-motion | ✓ Link | 0.113 | | | | | | | | | | pc4consistentdepth | 2023-04-18 |
Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps | ✓ Link | 0.115 | 4.698 | 0.192 | 0.785 | 0.871 | 0.959 | 0.982 | | | | Dyna-DM | 2022-06-08 |
Digging Into Self-Supervised Monocular Depth Estimation | ✓ Link | 0.115 | | | | | | | | | 1 | Monodepth2 M | 2019-10-01 |
Unsupervised Monocular Depth Estimation with Left-Right Consistency | ✓ Link | 0.133 | | | | | | | | | | Monodepth S | 2016-09-13 |
Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics | | 0.1412 | | | | | | | | | | Struct2Depth M | 2019-06-12 |