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Amodal Ground Truth and Completion in the Wild
April 30, 2024, 4:48 a.m. | Guanqi Zhan, Chuanxia Zheng, Weidi Xie, Andrew Zisserman
cs.CV updates on arXiv.org arxiv.org
Abstract: This paper studies amodal image segmentation: predicting entire object segmentation masks including both visible and invisible (occluded) parts. In previous work, the amodal segmentation ground truth on real images is usually predicted by manual annotaton and thus is subjective. In contrast, we use 3D data to establish an automatic pipeline to determine authentic ground truth amodal masks for partially occluded objects in real images. This pipeline is used to construct an amodal completion evaluation benchmark, …
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