Benchmark (up-to-date)
Public Benchmark
Disclaimer:
- This is just a benchmark on some standard datasets, which means the model does not necessarily become the actual “SOTA” for in-the-wild applications
- This benchmark focuses on accuracy metrics but no latency metrics, which are also an essential part of the real-time applications
Papers with Code - Monocular Depth Estimation
Personal Benchmark
Personal Notes
From depth estimation to Pseudo-LIDAR
Augmentation techniques for depth model
Prominent Works
These works may not be “SOTA” on some specific datasets but have a high potential for real-world, in-the-wild applications
Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera (2025)
Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimation (2024)
Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction (2024)
World-consistent Video Diffusion with Explicit 3D Modeling (2024)
RollingDepth: Video Depth without Video Models (2024)
https://github.com/prs-eth/rollingdepth
Depth Anything - CVPR 2024
https://github.com/DepthAnything/Depth-Anything-V2
https://github.com/LiheYoung/Depth-Anything
DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos (2024)
https://github.com/Tencent/DepthCrafter
Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation - Neurips 2024
https://github.com/albert100121/Depth-Anywhere
Depth Pro: Sharp Monocular Metric Depth in Less Than a Second (2024)
https://github.com/apple/ml-depth-pro
https://github.com/apple/ml-depth-pro/issues/1
UniDepth: Universal Monocular Metric Depth Estimation - CVPR 2024
https://github.com/lpiccinelli-eth/UniDepth
Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation - CVPR 2024
https://github.com/prs-eth/marigold
Booster: A Benchmark for Depth from Images of Specular and Transparent Surfaces (2023)
Deep Depth from Focus with Differential Focus Volume - CVPR 2022
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer (2020)
https://github.com/isl-org/MiDaS
Datasets & Simulator
RGBD Objects in the Wild: Scaling Real-World 3D Object Learning from RGB-D Videos
https://github.com/wildrgbd/wildrgbd
CARLA Simulator
https://github.com/carla-simulator/carla