| DeepLabV3+ (F10) |
- absolute relative error
- 0.110
|
Single Image Depth Estimation Trained via Depth from Defocus Cues 2020-01-14 |
코드 1 |
| DiPE |
- absolute relative error
- 0.112
|
DiPE: Deeper into Photometric Errors for Unsupervised Learning of Depth and Ego-motion from Monocular Videos 2020-03-03 |
코드 1 |
| DNet |
- absolute relative error
- 0.113
- RMSE
- 4.812
- RMSE log
- 0.191
- Delta < 1.25
- 0.877
- Delta < 1.25^2
- 0.960
- Delta < 1.25^3
- 0.981
|
Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications 2020-04-12 |
코드 1 |
| LSIM |
- absolute relative error
- 0.113
|
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation 2019-05-01 |
코드 1 |
| SC-Depth (ResNet 50) |
- absolute relative error
- 0.114
- RMSE
- 4.706
- RMSE log
- 0.191
- Delta < 1.25
- 0.873
- Delta < 1.25^2
- 0.960
- Delta < 1.25^3
- 0.982
|
Unsupervised Scale-consistent Depth Learning from Video 2021-05-25 |
코드 1 · 코드 2 |
| SemanticAware |
- absolute relative error
- 0.118
|
Towards Scene Understanding: Unsupervised Monocular Depth Estimation With Semantic-Aware Representation 2019-06-01 |
연결 없음 |
| SC-Depth (ResNet18) |
- absolute relative error
- 0.119
- RMSE
- 4.950
- RMSE log
- 0.197
- Delta < 1.25
- 0.863
- Delta < 1.25^2
- 0.957
- Delta < 1.25^3
- 0.981
|
Unsupervised Scale-consistent Depth Learning from Video 2021-05-25 |
코드 1 · 코드 2 |
| PackNet-SfM |
- absolute relative error
- 0.12
|
3D Packing for Self-Supervised Monocular Depth Estimation 2019-05-06 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| 3Net |
- absolute relative error
- 0.126
|
Learning monocular depth estimation with unsupervised trinocular assumptions 2018-08-05 |
코드 1 |
| SC-SfMLearner_CS+K |
- absolute relative error
- 0.128
|
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video 2019-08-28 |
코드 1 · 코드 2 |
| SelfDepthNorm |
- absolute relative error
- 0.133
|
Self-supervised Learning for Single View Depth and Surface Normal Estimation 2019-03-01 |
연결 없음 |
| SIGNet |
- absolute relative error
- 0.133
|
SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception 2018-12-13 |
코드 1 · 코드 2 |
| struct2depth |
- absolute relative error
- 0.135
|
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos 2018-11-15 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 |
| SC-SfMLearner |
- absolute relative error
- 0.137
|
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video 2019-08-28 |
코드 1 · 코드 2 |
| CC |
- absolute relative error
- 0.140
|
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation 2018-05-24 |
코드 1 |
| SIW |
- absolute relative error
- 0.14
|
Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings 2022-02-04 |
연결 없음 |
| LeReS |
- absolute relative error
- 0.149
- Delta < 1.25
- 0.784
|
Learning to Recover 3D Scene Shape from a Single Image 2020-12-17 |
코드 1 |
| GASDA |
- absolute relative error
- 0.149
|
Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation 2019-04-03 |
코드 1 |
| VDA |
- absolute relative error
- 0.193
|
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach 2019-03-26 |
코드 1 |