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• W3153807375 abstract "In this paper, we present a regression-based pose recognition method using cascade Transformers. One way to categorize the existing approaches in this domain is to separate them into 1). heatmap-based and 2). regression-based. In general, heatmap-based methods achieve higher accuracy but are subject to various heuristic designs (not end-to-end mostly), whereas regression-based approaches attain relatively lower accuracy but they have less intermediate non-differentiable steps. Here we utilize the encoder-decoder structure in Transformers to perform regression-based person and keypoint detection that is general-purpose and requires less heuristic design compared with the existing approaches. We demonstrate the keypoint hypothesis (query) refinement process across different self-attention layers to reveal the recursive self-attention mechanism in Transformers. In the experiments, we report competitive results for pose recognition when compared with the competing regression-based methods." @default.
• W3153807375 created "2021-04-26" @default.
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• W3153807375 date "2021-04-14" @default.
• W3153807375 modified "2023-09-26" @default.
• W3153807375 title "Pose Recognition with Cascade Transformers" @default.
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• W3153807375 doi "https://doi.org/10.48550/arxiv.2104.06976" @default.
• W3153807375 hasPublicationYear "2021" @default.
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