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title
MaskViT: Masked Visual Pre-Training for Video Prediction
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CoRL 2022 submission
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MaskViT
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2026-01-09 04:32:10
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MaskViT: Masked Visual Pre-Training for Video Prediction | MaskViT Skip to the content. MaskViT: Masked Visual Pre-Training for Video Prediction Agrim Gupta 1 , Stephen Tian 1 , Yunzhi Zhang 1 , Jiajun Wu 1 , Roberto Martín-Martín 2, 1 , Li Fei-Fei 1 1 Stanford University, 2 Salesforce AI arXiV Code Qualitative Results Real Robot Experiments MaskViT model diagram (your browser couldn't load the video). Abstract The ability to predict future visual observations conditioned on past observations and motor commands can enable embodied agents to plan solutions to a variety of tasks in complex environments. This work shows that we can create good video prediction models by pre-training transformers via masked visual modeling. Our approach, named MaskViT, is based on two simple design decisions. First, for memory and training efficiency, we use two types of window attention: spatial and spatiotemporal. Second, during training, we mask a va...
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