|Description (include details on usage, files and paper references)||The Cambridge-driving Labeled Video Database (CamVid) dataset from Gabriel Brostow [?] contains ten minutes of video footage and corresponding semantically labeled groundtruth images at intervals. There exist 32 semantic classes and 701 segmentation images.
There are multiple versions of this dataset. Browstows 101 frames CamSeq01 sequence at 920x720 resolution. The same by Ladicky at lower 320x240 resolution. And the whole three sequences in MFX files with 701 segs in total (over all three).
The package from Brostow also contains an InteractLabeler, paint stroke logs, color2label assignments and various statistics.
The dataset is typically used for semantic scene segmentation, and recently has also been augmented with multi-view reconstruction using 3D data as additional cue. However, only 11 semantic classes are used instead of the full 32 classes (namely: fixme)