Visual Question Answering Vqa On Illusionvqa
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Paper Title | Repository |
|---|---|---|---|
| GPT4-Vision | 58.85 | IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models | |
| LLaVA-1.5-13B | 40 | IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models | |
| Gemini-Pro | 51.26 | IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models | |
| InstructBLIP-13B | 34.25 | IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models | |
| Gemini-Pro 4-shot | 52.87 | IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models | |
| CogVLM | 38.16 | IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models | |
| GPT4-Vision 4-shot | 62.99 | IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models |
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