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AdaViT: Adaptive Tokens for Efficient Vision Transformer
A-ViT achieves this by automatically reducing the number of tokens in vision transformers that are processed in the network as inference proceeds.
DecomposeMe: Simplifying ConvNets for End-to-End Learning
Deep learning and convolutional neural networks (ConvNets) have been successfully applied to most relevant tasks in the computer vision community.
Motion Estimation via Robust Decomposition with Constrained Rank
To this end we propose the Robust Decomposition with Constrained Rank (RD-CR), a proximal gradient based method that enforces the rank constraints inherent to motion estimation.
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