[OSPP] Proposal for Unknown Task Recognition Algorithm Reproduction based on Lifelong Learning of Ianvs #41
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Signed-off-by: Frank-lilinjie <lilinjie@bupt.edu.cn>
Signed-off-by: Frank-lilinjie <lilinjie@bupt.edu.cn>
Signed-off-by: Frank-lilinjie <lilinjie@bupt.edu.cn>
MooreZheng
reviewed
Oct 25, 2022
| 1. Reproducing the algorithm from the CVPR2021 paper "Learning placeholders for open-set recognition". | ||
| 2. Achieving an accuracy of 0.9 for unknown task recognition. | ||
| 3. Making unknown category recognition modules according to Ianvs architecture and contextual relationship to store in the lib library, so that the algorithm can be used on demand. | ||
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Add test report in goals #26 (comment)
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Received and completed it.
Signed-off-by: Frank-lilinjie <lilinjie@bupt.edu.cn>
Signed-off-by: Frank-lilinjie <lilinjie@bupt.edu.cn>
Signed-off-by: Frank-lilinjie <lilinjie@bupt.edu.cn>
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/lgtm |
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The PR is perfect, but there are some minor issues about git commit convention that should be noted. For commit history of Ianvs repository more readable and cleaner, I suggest to squash the commits by More details can be refered as following:
these are just some examples, you can write it according to your commit content. |
This was referenced Feb 22, 2023
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Sep 25, 2024
[OSPP] Proposal for Unknown Task Recognition Algorithm Reproduction based on Lifelong Learning of Ianvs
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Proposal for Unknown Task Recognition Algorithm Reproduction based on Lifelong Learning of Ianvs.
This PR is a proposal that project aims to reproduce the CVPR2021 paper "Learning placeholders for open-set recognition" in the Semantic Segmentation dataset. This paper proposes placeholders that imitate the emergence of new classes, thus helping to transform closed-set training into open-set training.
This PR is a modification of the last PR