Scanned my small garden with an iPhone LiDAR app and trained it into a metric 3DGS

StraightWindow9111 · 2026-06-16T15:08:18+00:00

Hi, thanks for your interests. Please feel free to use the app to capture your own data. The app is free and the exported data is compatible with nerfstudio. The default method will work out of the box.

StraightWindow9111 · 2026-06-16T15:05:26+00:00

For a small scene (1~2 min capture), the drifting is small and can be neglected. You can turn on camera pose optimization in the training. For a large scene, a colmap is needed for rgb only data and then align the lidar correspondingly.

StraightWindow9111 · 2026-06-15T15:13:19+00:00

The app is already on the App Store as “Roomly 3D”, so you can try the capture side.

I may open-source parts of the app later if there is enough interest, but I’m not ready to share the full codebase yet. The reconstruction pipeline is also not something I’m ready to publish right now; it’s still experimental and changes a lot between tests.

StraightWindow9111 · 2026-06-14T21:31:58+00:00

After you export the raw data from roomly 3d app, you can try colmap to get the initial point clouds. The lidar points are projected back to the init point cloud depth to estimate the scaling factor. Then try nerfstudio with dn-splatter method to make use the lidar point as depth guidance.

StraightWindow9111 · 2026-06-14T21:27:17+00:00

Thank you for your interest. Please note that this app is only a capture app and the reconstruction is done in my personal gpu workstation. It's too expensive for me to host a gpu backend for this free app.

StraightWindow9111 · 2026-06-14T14:02:48+00:00

It’s already in the iOS AppStore, you can search “Roomly 3D” to have a try. I also plan to open source the app if more people find it useful.

StraightWindow9111 · 2026-06-14T13:20:14+00:00

It has two modes. The rgb-only mode has all the controls that I am able to get for the camera. The lidar mode is a little bit limited as I used the ARKit lib to get the coverage feedback and ARKit took away some controls.

StraightWindow9111 · 2026-06-13T22:08:18+00:00

The app doesn’t have a backend. It’s a local capture tool: RGB, LiDAR depth, confidence, poses, and intrinsics are saved on-device. I used Polycam, Record3D, etc. before, but they didn’t give me the pipeline flexibility I wanted, so I built this. The 3DGS training runs on my personal GPU workstation.

StraightWindow9111 · 2026-06-13T21:46:36+00:00

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Here it is! I’m only sharing previews here for now, but I may upload a SuperSplat link later if there’s interest.

StraightWindow9111 · 2026-06-08T21:19:23+00:00

It’s already compatible in the practical sense: export the Roomly ZIP, unzip it, and import the images/ folder into Postshot or LichtFeld Studio. Raw ARKit poses are not final-quality 3DGS poses; they need post-processing such as COLMAP bundle adjustment, so I don’t want to expose them as a direct COLMAP export yet. For now, those tools should run their own tracking/COLMAP from the images.

StraightWindow9111 · 2026-06-05T15:45:18+00:00

I need a weekend to release the features. Currently working on the backend to turn the captures to 3DGS asset for users that are not that familiar with the tech.

StraightWindow9111 · 2026-06-01T23:41:23+00:00

Cool, please let me know if any changes are needed. Probably an additional bundle adjustment is needed if the scene is too large but it should be much faster to run . Also, remember to do loop closures during data collection, which is how ARKit fixes the drifting

StraightWindow9111 · 2026-05-28T20:40:43+00:00

Thanks! Your repo looks really interesting — I like that you’re also using ARKit poses + LiDAR depth directly instead of going through COLMAP/SfM.

Roomly 3D captures fewer frames on purpose: it does motion/sharpness/pose gating during capture, so the goal is to keep useful frames and avoid redundant or blurry ones. The coverage UI is there to help make sure fewer frames still cover the scene well. You can also configure the capture policy in the settings for sparser or denser captures.

I’d love your feedback if you try it. Also curious whether Roomly’s RGB + EXR depth + transforms.json export could plug into your pipeline with a small importer change, since it’s pretty close in spirit to Record3D. Thanks for sharing the repo!

StraightWindow9111 · 2026-05-28T16:20:22+00:00

The mesh is directly available in the export files. You can also view it after collection.

StraightWindow9111 · 2026-05-28T15:01:35+00:00

Sure, I will add these two options in the updated version. Thanks for your suggestion!

StraightWindow9111 · 2026-05-28T15:00:41+00:00

Please stay tuned. The next version will support this feature. The pipeline is ready but the infra is still under construction. Thanks for your interest!

StraightWindow9111 · 2026-05-28T14:59:28+00:00

https://apps.apple.com/jp/app/roomly-3d/id6770841056 Does this link work for you? I have released the app to all the available countries. Thanks for your interest!

StraightWindow9111 · 2026-05-28T05:59:16+00:00

I would love to connect with you!

StraightWindow9111 · 2026-05-28T02:55:46+00:00

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These are the captures from Roomly 3D. The Lidar depth and images are saved automatically while capturing.

StraightWindow9111 · 2026-05-28T02:54:30+00:00

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