IllusionVQA
Introduced by Shahgir et al. in IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models
IllusionVQA is a Visual Question Answering (VQA) dataset with two sub-tasks. The first task tests comprehension on 435 instances in 12 optical illusion categories. Each instance consists of an image with an optical illusion, a question, and 3 to 6 options, one of which is the correct answer. We refer to this task as Logo IllusionVQA-Comprehension. The second task tests how well VLMs can differentiate geometrically impossible objects from ordinary objects when two objects are presented side by side. The task consists of 1000 instances following a similar format to the first task. We refer to this task as Logo IllusionVQA-Soft-Localization.
Benchmarks
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IllusionVQA
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GPT4-Vision 4-shot+CoT
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IllusionVQA
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GPT4-Vision
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Papers
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