ODMS (Object Depth via Motion and Segmentation)
Introduced by Griffin et al. in Learning Object Depth from Camera Motion and Video Object Segmentation
ODMS is a dataset for learning Object Depth via Motion and Segmentation. ODMS training data are configurable and extensible, with each training example consisting of a series of object segmentation masks, camera movement distances, and ground truth object depth. As a benchmark evaluation, the dataset provides four ODMS validation and test sets with 15,650 examples in multiple domains, including robotics and driving.
Source: https://github.com/griffbr/ODMSPapers
| Paper | Code | Results | Date | Stars |
|---|
