This dataset contains multi-view images for 300 3D objects that are rigid and sufficiently textured. Each 3D object has ~250 images (1280 by 720 pixels) captured from different viewpoints with a clean background, using a turntable and a webcam (with a fixed focal length 1000 pixels). The dataset can be used for research on 3D reconstruction and object recognition.
The data for each 3D object is provided in a separate folder, which contains:
1) a "db_img" subfolder for the multi-view images of the object;
2) a "list_db_img.txt" file that lists the filenames of the images;
3) a "model.nvm" file containing an example 3D point cloud model reconstructed from the images using VisualSFM toolkit (http://homes.cs.washington.edu/~ccwu/vsfm/). The model file (after copied to the image subfolder) can be opened with VisualSFM to show a possible 3D representation of the object. You can freely reconstruct other 3D models by yourself.
Since the size of this dataset is large (~23GB), we partition it into 12 parts, each of which (<2GB) can be downloaded and decompressed separately from:
We would appreciate it if you cite the following paper when using the dataset:
Qiang Hao, Rui Cai, Zhiwei Li, Lei Zhang, Yanwei Pang, Feng Wu, and Yong Rui. "Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition". in Proc. of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2013), pp.899-906, Portland, Oregon, USA. June 23-28, 2013.
If you have questions about the dataset, please contact Qiang Hao (email: firstname.lastname@example.org).