text: Table 1 Pixels vs. Featurized Targets. We ablate the effect of computing the prediction loss in feature space vs pixel space. All 
  models are trained on VideoMix2M for 90K iterations with a batch size of 3072 using the multi-block prediction task. We 
  examine downstream performance using a frozen backbone with attentive probing, and report top-1 accuracy using a single 
  center view. We also examine end-to-end fine-tuning performance of the models on K400. Predicting in feature space provide 
  a consistent improvement over pixel space prediction. 