SaaSHub helps you find the best software and product alternatives Learn more →
Top 23 depth-estimation Open-Source Projects
-
Depth-Anything
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
-
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
-
-
PatchFusion
[CVPR 2024] An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
-
-
-
MonoRec
Official implementation of the paper: MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera (CVPR 2021)
-
Insta-DM
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency (AAAI 2021)
-
-
deep-video-mvs
Code for "DeepVideoMVS: Multi-View Stereo on Video with Recurrent Spatio-Temporal Fusion" (CVPR 2021)
-
SGDepth
[ECCV 2020] Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
-
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)
-
STEPS
This is the official repository for ICRA-2023 paper "STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth Estimation"
-
calibrated-backprojection-network
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
-
merged_depth
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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...
For a long time, the state-of-the-art models for monocular depth estimation such as DORN and DenseDepth were built with convolutional neural networks. Recently, however, both transformer-based models such as DPT and GLPN, and diffusion-based models like Marigold have achieved remarkable results!
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/).
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
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?
-
Software 3D scanner. Free on Prusa Printables
-
A note from our sponsor - SaaSHub
www.saashub.com | 1 May 2024
Index
What are some of the best open-source depth-estimation projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | Depth-Anything | 5,701 |
| 2 | monodepth2 | 3,977 |
| 3 | ZoeDepth | 1,959 |
| 4 | DenseDepth | 1,533 |
| 5 | OpenSeeFace | 1,318 |
| 6 | simplerecon | 1,205 |
| 7 | PatchFusion | 892 |
| 8 | 3D-Reconstruction-with-Deep-Learning-Methods | 853 |
| 9 | Monocular-Depth-Estimation-Toolbox | 847 |
| 10 | zed-sdk | 710 |
| 11 | AdaBins | 673 |
| 12 | manydepth | 594 |
| 13 | MonoRec | 565 |
| 14 | stereoDepth | 240 |
| 15 | Insta-DM | 221 |
| 16 | DiverseDepth | 216 |
| 17 | awesome-NeRF | 212 |
| 18 | deep-video-mvs | 205 |
| 19 | SGDepth | 194 |
| 20 | unsupervised-depth-completion-visual-inertial-odometry | 183 |
| 21 | STEPS | 165 |
| 22 | calibrated-backprojection-network | 110 |
| 23 | merged_depth | 45 |
Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com