This is the Linux app named VGGSfM whose latest release can be downloaded as vggsfmsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named VGGSfM with OnWorks for free.
Suivez ces instructions pour exécuter cette application :
- 1. Téléchargé cette application sur votre PC.
- 2. Entrez dans notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous voulez.
- 3. Téléchargez cette application dans ce gestionnaire de fichiers.
- 4. Démarrez l'émulateur en ligne OnWorks Linux ou Windows en ligne ou l'émulateur en ligne MACOS à partir de ce site Web.
- 5. Depuis le système d'exploitation OnWorks Linux que vous venez de démarrer, accédez à notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous souhaitez.
- 6. Téléchargez l'application, installez-la et exécutez-la.
CAPTURES D'ÉCRAN
Ad
VGGSfM
DESCRIPTION
VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. Version 2.0 adds support for dynamic scene handling, dense point cloud export, video-based reconstruction (1000+ frames), and integration with Gaussian Splatting pipelines. It leverages tools like PyCOLMAP, poselib, LightGlue, and PyTorch3D for feature matching, pose estimation, and visualization. With minimal configuration, users can process single scenes or full video sequences, apply motion masks to exclude moving objects, and train neural radiance or splatting models directly from reconstructed outputs.
Comment ça marche
- End-to-end 3D reconstruction from images or videos with automatic camera pose estimation
- Outputs in standard COLMAP format compatible with NeRF and Gaussian Splatting pipelines
- Supports over 1000 sequential frames with sliding-window video processing
- Handles dynamic/moving scenes via optional binary masks
- Exports dense point clouds and dense depth maps (beta)
- Easily integrates with gsplat for Gaussian Splat training
- Interactive visualization using Gradio or Visdom
- Pretrained model auto-downloaded from Hugging Face or Google Drive
Langage de programmation
Python, shell Unix
Catégories
This is an application that can also be fetched from https://sourceforge.net/projects/vggsfm.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
