After deleting a whole object from an indoor scene, the frozen SR-JEPA predictor imputes a latent that identifies the object's class at 43.13% macro accuracy, 22.18 points above the strongest floor.
data2vec: A general framework for self-supervised learning in speech, vision and language
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SR-JEPA: Learning Predictive Latent State in 3D Scenes
After deleting a whole object from an indoor scene, the frozen SR-JEPA predictor imputes a latent that identifies the object's class at 43.13% macro accuracy, 22.18 points above the strongest floor.