Video pretraining can be as efficient as image pretraining when you remove unnecessary architectural complexity—a single encoder with the right loss function learns better representations faster than methods requiring asymmetric branches or exponential-moving-average targets.
LeVJEPA is a video pretraining method that eliminates computational inefficiencies in existing approaches by using a single encoder with a mathematically-guaranteed collapse-prevention mechanism, instead of complex architectural tricks like target encoders or masked reconstruction.