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README.md
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@@ -33,6 +33,7 @@ The R2SM dataset is constructed using images and annotations adapted from the fo
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- **COCOA-cls** and **D2SA**: From *Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation (WACV 2019)* by Follmann et al.
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- **MUVA**: From *MUVA: A New Large-Scale Benchmark for Multi-view Amodal Instance Segmentation in the Shopping Scenario (ICCV 2023)* by Li et al.
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- Licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
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All images and annotations are originally released under non-commercial academic licenses, and R2SM is released under the same usage restriction.
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Please refer to the original datasets for full details.
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- **COCOA-cls** and **D2SA**: From *Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation (WACV 2019)* by Follmann et al.
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- **MUVA**: From *MUVA: A New Large-Scale Benchmark for Multi-view Amodal Instance Segmentation in the Shopping Scenario (ICCV 2023)* by Li et al.
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- Licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
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- License link: https://creativecommons.org/licenses/by-nc/4.0/
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All images and annotations are originally released under non-commercial academic licenses, and R2SM is released under the same usage restriction.
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Please refer to the original datasets for full details.
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