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Hybrid with 7×7 synthetic light field views✖️: PSNR😞>=32dB
RK
Model
PSNR ↑ {Input fr.}
Training dataset
Official repository
Practical model
VapourSynth
1
LFVRT MDE: DPT Backbone: ViT
32.66 {3+1D}
GoPro & TAMULF
MDE:
-
-
📝 Note: The above ranking includes only one model, as the other methods are image-based and don't have any temporal information making them unsuitable for light field video reconstruction from monocular video.
Appendix 3: List of all research papers from the above rankings
Method
Paper
Venue
Depth Anything
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
DPT
Vision Transformers for Dense Prediction
FutureDepth
FutureDepth: Learning to Predict the Future Improves Video Depth Estimation
GBDMF
Multi-Resolution Monocular Depth Map Fusion by Self-Supervised Gradient-Based Composition
GenPercept
Diffusion Models Trained with Large Data Are Transferable Visual Models
LeReS
Learning to Recover 3D Scene Shape from a Single Image
LightedDepth
LightedDepth: Video Depth Estimation in light of Limited Inference View Angles
LFVRT
Synthesizing Light Field Video from Monocular Video
Marigold
Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
Metric3D
Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image
Metric3D v2
Metric3D v2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation
MiDaS
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer
MiDaS v3.1
MiDaS v3.1 – A Model Zoo for Robust Monocular Relative Depth Estimation
NeWCRFs
Neural Window Fully-connected CRFs for Monocular Depth Estimation
PatchFusion
PatchFusion: An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation
R + AL
High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation