Super-CLEVR
Introduced by Li et al. in Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning
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.
Source: Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual ReasoningPapers
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