The first dataset for learning Object Depth via Motion and Detection
ODMD Dataset
ODMD is the first dataset for learning Object Depth via Motion and Detection. ODMD training data are configurable and extensible, with each training example consisting of a series of object detection bounding boxes, camera movement distances, and ground truth object depth. As a benchmark evaluation, we provide four ODMD validation and test sets with 21,600 examples in multiple domains, and we also convert 15,650 examples from the ODMS benchmark for detection. In our paper, we use a single ODMD-trained network with object detection or segmentation to achieve state-of-the-art results on existing driving and robotics benchmarks and estimate object depth from a camera phone, demonstrating how ODMD is a viable tool for monocular depth estimation in a variety of mobile applications.
Depth results using a camera phone.