Web: http://arxiv.org/abs/2209.09545

Sept. 21, 2022, 1:13 a.m. | Dong Zhang, Jinhui Tang, Kwang-Ting Cheng

cs.CV updates on arXiv.org arxiv.org

Capturing the long-range dependencies has empirically proven to be effective
on a wide range of computer vision tasks. The progressive advances on this
topic have been made through the employment of the transformer framework with
the help of the multi-head attention mechanism. However, the attention-based
image patch interaction potentially suffers from problems of redundant
interactions of intra-class patches and unoriented interactions of inter-class
patches. In this paper, we propose a novel Graph Reasoning Transformer (GReaT)
for image parsing to enable …

arxiv graph image parsing reasoning transformer

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