In contrast to conventional computer vision methods, which require humans to manually label thousands or even millions of images, building
video prediction models only requires unannotated video, which can be collected by the robot entirely autonomously.
Indeed,
video prediction models have also been applied to datasets that represent everything from human activities to driving, with compelling results.
Not exact matches
In this research, the DNNs were trained with natural scene
videos of motion from the point of view of the viewer, and the motion
prediction ability of the obtained computer
model was verified using a rotating propeller in unlearned
videos and the «Rotating Snake Illusion.»
The
video above provides a view of one simulation generated on Aug. 27 by the HWRF
model, developed by the National Centers for Environmental
Prediction and National Weather Service.