A Dataset of 371 3D Models of Everyday tabletop objects along with their 320,000 Real World RGB and Depth Images

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Computer Vision

Artificial Intelligence

A Dataset of 371 3D Models of Everyday tabletop objects along with their 320,000 Real World RGB and Depth Images

A Real World Dataset for Multi-view 3D Reconstruction

We present a dataset of 371 3d models of everyday tabletop objects along with their 320,000 real world rgb and depth images along with their 320,000 real world rgb and depth images.

Accurate annotations of cameraposes and object poses for each image are performed in a semi-automated fashion to facilitate the use of the dataset for myriad 3d applications like shapereconstruction, object pose estimation, shape retrieval etc.

We primarily focus on learned multi-view 3d reconstruction due to the lack of appropriate realworld benchmark for the task and demonstrate that our dataset can fill that gap.

We present a dataset of 371 3d models of everyday tabletop objects along with their 320,000 real world rgb and depth images along with their 320,000 real world rgb and depth images.

We primarily focus on learned multi-view 3d reconstruction due to the lack of appropriate realworld benchmark for the task and demonstrate that our dataset can fill that gap.

Authors

Rakesh Shrestha, Siqi Hu, Minghao Gou, Ziyuan Liu, Ping Tan

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