Common Objects in 3D
Introduced by Reizenstein et al. in Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction
Common Objects in 3D is a large-scale dataset with real multi-view images of object categories annotated with camera poses and ground truth 3D point clouds. The dataset contains a total of 1.5 million frames from nearly 19,000 videos capturing objects from 50 MS-COCO categories and, as such, it is significantly larger than alternatives both in terms of the number of categories and objects.
Source: Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category ReconstructionBenchmarks
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