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Top 18 Python depth-estimation Projects
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Depth-Anything
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
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InfluxDB
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PatchFusion
[CVPR 2024] An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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MonoRec
Official implementation of the paper: MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera (CVPR 2021)
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Insta-DM
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency (AAAI 2021)
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deep-video-mvs
Code for "DeepVideoMVS: Multi-View Stereo on Video with Recurrent Spatio-Temporal Fusion" (CVPR 2021)
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SGDepth
[ECCV 2020] Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
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unsupervised-depth-completion-visual-inertial-odometry
Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
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STEPS
This is the official repository for ICRA-2023 paper "STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth Estimation"
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calibrated-backprojection-network
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
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merged_depth
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
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learning-topology-synthetic-data
Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
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Depth estimation improved a lot as well e.g. with Depth-Anything [0]. But those are mostly relative depth instead of metric. Also when even converted to metric they still seems have a lot of pointclouds at the edges that have to be pruned - visible in this blog [1]. Looks like those models trained on Lidar or Stereo depthmaps that has this limitations. I think we don't have enough clean training data for 3d unless we maybe train on synthetic data (then we can have plenty, generate realistic scene in Unreal Engine 5 and train on rendered 2d frames)
[0] https://github.com/LiheYoung/Depth-Anything
[1] https://medium.com/@patriciogv/the-state-of-the-art-of-depth...
Project mention: PATCHFUSION is really impressive. High resolution depth maps in 16bit. I've been waiting for this. https://github.com/zhyever/PatchFusion | /r/StableDiffusion | 2023-12-09
Yup! This kind of reconstruction is known as multi-view reconstruction. Though the cameras don't need to have a movable mount, they're already on a car which moves! The car moves and gives them a new "perspective" at every frame. That's how some monocular systems already work. Here's an example of one such system: https://github.com/nianticlabs/manydepth
That said, I think what you're referring to is more extreme perspectives that shift in ways the car cannot drive and you are correct that this would aid in reconstruction. This is how NERF models do their 3D reconstruction (https://nerfies.github.io/).
Python depth-estimation related posts
- Video generation models as world simulators
- Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
- Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
- Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
- PATCHFUSION is really impressive. High resolution depth maps in 16bit. I've been waiting for this. https://github.com/zhyever/PatchFusion
- How Many Sensors for Autonomous Driving?
- This may be a silly question but can I hire someone to make me a customized avatar for vr chat?
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Index
What are some of the best open-source depth-estimation projects in Python? This list will help you:
Project | Stars | |
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1 | Depth-Anything | 5,594 |
2 | OpenSeeFace | 1,312 |
3 | simplerecon | 1,202 |
4 | PatchFusion | 887 |
5 | Monocular-Depth-Estimation-Toolbox | 847 |
6 | AdaBins | 673 |
7 | manydepth | 594 |
8 | MonoRec | 565 |
9 | stereoDepth | 240 |
10 | Insta-DM | 220 |
11 | DiverseDepth | 216 |
12 | deep-video-mvs | 205 |
13 | SGDepth | 194 |
14 | unsupervised-depth-completion-visual-inertial-odometry | 183 |
15 | STEPS | 165 |
16 | calibrated-backprojection-network | 110 |
17 | merged_depth | 45 |
18 | learning-topology-synthetic-data | 37 |
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