Object Pose Estimation - Groups

Rigidity Preserving Image Transformations and Equivariance in Perspective

The dataset used in the paper is the LINEMOD and Occlusion LINEMOD datasets, which are used for 6D object pose estimation.

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YCB-V

The YCB-V dataset contains 21 objects with complex shapes and occlusions.

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LM-O

The LM-O dataset consists of 1214 images and is used as a test dataset for 6DoF object pose estimation. The dataset includes 8 objects with partial occlusion.

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YCB-Video dataset

The YCB-Video dataset contains 92 videos of 21 objects with varying textures and sizes under cluttered indoor environments.

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LINEMOD-OCCLUSION dataset

The LMO dataset is a subset of the LM dataset consisting of eight objects in more cluttered scenes.

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LINEMOD dataset

The LM consists of 13 objects with approximately 1.2K images per object. We follow the settings described in [2], which uses 15% of the data for training and the rest for testing.

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Occlusion LineMOD

The dataset used in the paper for 6Dof object pose estimation using RGB-D images.

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YCB-Video

The dataset used for 6D object pose estimation, consisting of images of 16 objects with varying levels of occlusion.

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8 datasets found