Under a fixed 80k-update budget, DINOv2 dominates semantic benchmarks, VideoMAE dominates geometric ones, and their combination balances the two at a measurable cost.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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A Controlled Study of Self-Supervised Image and Video Pretraining under Limited Resources
Under a fixed 80k-update budget, DINOv2 dominates semantic benchmarks, VideoMAE dominates geometric ones, and their combination balances the two at a measurable cost.