WebFeb 13, 2024 · In this paper, we linearize Transformers free from specific inductive biases based on the flow network theory. We cast attention as the information flow aggregated from the sources (values) to the sinks (results) through the learned flow capacities (attentions). Within this framework, we apply the property of flow conservation with attention ... Web本文解读港中文 MMLab 在 ECCV 2024 上发表的论文《FlowFormer: A Transformer Architecture for Optical Flow》。 这项工作提出了 FlowFormer 算法将 Transformer 结构结合进光流估计的框架中，显著提升了光流估 …

Accepted papers ECCV2024

WebFlowFormer, a transformer-based architecture that encodes and decodes the 4D cost volume to achieve accurate optical flow estimation. In Fig. 1, we show the overview … WebFlowFormer: A Transformer Architecture for Optical Flow Zhaoyang Huang (Chinese University of HongKong)*; Xiaoyu Shi (CUHK); Chao Zhang (Samsung … how to stabilize wood for turning

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WebMar 26, 2024 · We introduce Recurrent All-Pairs Field Transforms (RAFT), a new deep network architecture for optical flow. RAFT extracts per-pixel features, builds multi-scale 4D correlation volumes for all pairs of pixels, and iteratively updates a flow field through a recurrent unit that performs lookups on the correlation volumes. RAFT achieves state-of … 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 … WebMar 2, 2024 · Abstract: 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. Inspired by the recent success of masked autoencoding (MAE) pretraining in unleashing transformers' capacity of encoding visual ... how to stable pets wow