We can create images with ground truth labels to be used for object detection and recognition research. We provide high quality labeling. Many just provide captions, which specify that the object is present somewhere in the image. However, more detailed information, such as bounding boxes, polygons or segmentation masks, is tremendously helpful.
- Experience in the tens of thousands of hours of work on annotation frames
- Accurate labeling by frames
- Important labeling for ADAS systems

Storing of labeling

The images and annotations are organized into folders. We indicate the sources of the images and annotations in the folder name and in the XML annotation files.

High quality labeled annotations

Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination.

We described image annotations that was used to label the identity of objects and where they occur in images. We worked on a few projects that had large number of images and we collected a large number of high quality annotations, spanning many different object categories, for a large set of images, many of which are high resolution. We presented results of the dataset contents showing the quality, breadth, and depth of the dataset.

High amount of information’s on every annotation.

We use object annotations across image database for building a model of 3D scenes. With this extra information, we are able to recover the 3D layout of the scene and learn about other spatial properties of scenes in 3D from 2D images.