Datasets › AMT Objects

AMT Objects

Introduced by Philipp Henzler et al. in Unsupervised Learning of 3D Object Categories from Videos in the Wild30 Mar 2021 archive 2025-07-28

AMT Objects is a large dataset of object centric videos suitable for training and benchmarking models for generating 3D models of objects from a small number of photos of the objects. The dataset consists of multiple views of a large collection of object instances.

The dataset contains 7 object categories from the MS COCO classes: apple, sandwich, orange, donut, banana, carrot and hydrant. For each class, annotators were asked to collect a video by looking ‘around’ a class instance, resulting in a turntable video. The dataset contains 169-457 videos per class. For each class, the videos were randomly split into training and testing videos in an 8:1 ratio.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • AMT Objects

1 variant name, as the archive lists them.

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