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FlowFormer: A Transformer Architecture for Optical Flow
WebFlowformer (ICML 2024) Flowformer: Linearizing Transformers with Conservation Flows Transformers have achieved impressive success in various areas. However, the attention mechanism has a quadratic complexity, significantly impeding Transformers from dealing with numerous tokens and scaling up to bigger models. WebMar 2, 2024 · FlowFormer introduces a transformer architecture into optical flow estimation and achieves state-of-the-art performance. The core component of FlowFormer is the transformer-based cost-volume encoder. hauser services middlefield ohio
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WebFlowFormer [huang2024flowformer] introduces a transformer architecture into optical flow estimation and achieves state-of-the-art performance. The core component of FlowFormer is the transformer-based cost-volume encoder. Inspired by the recent success of masked autoencoding (MAE) pretraining in unleashing transformers’ capacity of encoding visual … WebarXiv.org e-Print archive WebMar 30, 2024 · FlowFormer tokenizes the 4D cost volume built from an image pair, encodes the cost tokens into a cost memory with alternate-group transformer (AGT) layers in a novel latent space, and decodes the cost memory via a recurrent transformer decoder with dynamic positional cost queries. borderlands keyboard layout