Scene reconstruction / multiview(multiview reconstruction) / 3D Face Animation
Multi-View Stereo Reconstruction
- Multiview stereo data sets: a set of images
Multi-view Visual Geometry group’s data set
- Dinosaur, Model House, Corridor, Aerial views, Valbonne Church, Raglan Castle, Kapel sequence
Oxford reconstruction data set (building reconstruction)
- Oxford colleges
Multi-View Stereo dataset (Vision Middlebury)
- Temple, Dino
Multi-View Stereo for Community Photo Collections
- Venus de Milo, Duomo in Pisa, Notre Dame de Paris
- Dataset provided by Center for Machine Perception
- CVLab dense multi-view stereo image database
- Objects viewed from 144 calibrated viewpoints under 3 different lighting conditions
Object Recognition in Probabilistic 3D Scenes
- Images from 19 sites collected from a helicopter flying around Providence, RI. USA. The imagery contains approximately a full circle around each site.
- 24 scenarios recorded with 8 IP video cameras. The first 22 first scenarios contain a fall and confounding events, the last 2 ones contain only confounding events.
- 15 wide baseline stereo image pairs with large viewpoint change, provided ground truth homographies.
KTH Multiview Football Dataset II
- This dataset consists of 8000+ images of professional footballers during a match of the Allsvenskan league. It consists of two parts: one with ground truth pose in 2D and one with ground truth pose in both 2D and 3D.
Disney Research light field datasets
- This dataset includes: camera calibration information, raw input images we have captured, radially undistorted, rectified, and cropped images, depth maps resulting from our reconstruction and propagation algorithm, depth maps computed at each available view by the reconstruction algorithm without the propagation applied.
- Multiple people social interaction dataset captured by 500+ synchronized video cameras, with 3D full body skeletons and calibration data.
- 24 synthetic scenes. Available data per scene: 9x9 input images (512x512x3) , ground truth (disparity and depth), camera parameters, disparity ranges, evaluation masks.