Super-CLEVR is a dataset for Visual Question Answering (VQA) where different factors in VQA domain shifts can be isolated in order that their effects can be studied independently. It contains 21 vehicle models belonging to 5 categories, with controllable attributes. Four factors are considered: visual complexity, question redundancy, concept distribution and concept compositionality.
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PoseScript is a dataset that pairs a few thousand 3D human poses from AMASS with rich human-annotated descriptions of the body parts and their spatial relationships. This dataset is designed for the retrieval of relevant poses from large-scale datasets and synthetic pose generation, both based on a textual pose description.
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Super-CLEVR-3D is a visual question answering (VQA) dataset where the questions are about the explicit 3D configuration of the objects from images (i.e. 3D poses, parts, and occlusion). It consists of objects from 5 categories: aeroplanes, buses, bicycles, cars and motorbikes. The rendered objects are from CGParts dataset, with the same setting as Super-CLEVR dataset.