Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Conditional Link Prediction of Category-Implicit Keypoint Detection   Keypoints of objects reflect their concise abstractions, while the
corresponding connection links (CL) build the skeleton by detecting the
intrinsic relations between keypoints. Existing approaches are typically
computationally-intensive, inapplicable for instances belonging to multiple
classes, and/or infeasible to simultaneously encode connection information. To
address the aforementioned issues, we propose an end-to-end category-implicit
Keypoint and Link Prediction Network (KLPNet), which is the first approach for
simultaneous semantic keypoint detection (for multi-class instances) and CL
rejuvenation. In our KLPNet, a novel Conditional Link Prediction Graph is
proposed for link prediction among keypoints that are contingent on a
predefined category. Furthermore, a Cross-stage Keypoint Localization Module
(CKLM) is introduced to explore feature aggregation for coarse-to-fine keypoint
localization. Comprehensive experiments conducted on three publicly available
benchmarks demonstrate that our KLPNet consistently outperforms all other
state-of-the-art approaches. Furthermore, the experimental results of CL
prediction also show the effectiveness of our KLPNet with respect to occlusion
problems.

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The categories of this paper are: nlin
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The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
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The categories of this paper are: atom-ph
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The categories of this paper are: solv-int
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The categories of this paper are: cond-mat
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The categories of this paper are: eess
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The categories of this paper are: math-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: q-fin
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The categories of this paper are: ao-sci
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The categories of this paper are: nucl-ex
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The categories of this paper are: supr-con
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The categories of this paper are: funct-an
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The categories of this paper are: q-bio