Datasets:
Tasks:
Visual Question Answering
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
ArXiv:
License:
Update README.md
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README.md
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- benchmark
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configs:
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- config_name: OPTICS-CNT
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data_dir: OPTICS-CNT/
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- config_name: OPTICS-CMP
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data_dir: OPTICS-CMP/
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---
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<h1 align="center">OPTICS: Commonsense Reasoning over Visual Object Properties</h1>
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Inspired by human object categorization, OPTICS (formerly ORBIT) is a benchmark suite for evaluating how Vision–Language Models (VLMs) perceive and reason about object properties. It spans four object property dimensions (physical, taxonomic, functional, relational), three levels of reasoning complexity (direct recognition, property inference, counterfactual reasoning), and three image types (photographic/real, animated, AI-generated). It has two parts: **OPTICS-CNT** (exact counting) and **OPTICS-CMP** (count comparison).
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-
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📚 [arXiv](https://arxiv.org/abs/2508.10956) |
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💻 [Code](https://github.com/AbhishekKolari/OPTICS)
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</div>
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```
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OPTICS-CNT/
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├──
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└── <benchmark>.json
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OPTICS-CMP/
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├──
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└── <
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```
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### OPTICS-CNT
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- benchmark
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configs:
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- config_name: OPTICS-CNT
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data_dir: OPTICS-CNT/data
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- config_name: OPTICS-CMP
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data_dir: OPTICS-CMP/merged_images
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---
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<h1 align="center">OPTICS: Commonsense Reasoning over Visual Object Properties</h1>
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Inspired by human object categorization, OPTICS (formerly ORBIT) is a benchmark suite for evaluating how Vision–Language Models (VLMs) perceive and reason about object properties. It spans four object property dimensions (physical, taxonomic, functional, relational), three levels of reasoning complexity (direct recognition, property inference, counterfactual reasoning), and three image types (photographic/real, animated, AI-generated). It has two parts: **OPTICS-CNT** (exact counting) and **OPTICS-CMP** (count comparison).
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📄 [Paper](https://arxiv.org/pdf/2508.10956) |
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📚 [arXiv](https://arxiv.org/abs/2508.10956) |
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💻 [Code](https://github.com/AbhishekKolari/OPTICS)
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</div>
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```
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OPTICS-CNT/
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├── data/ # images + metadata.csv per image type
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└── <benchmark>.json
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OPTICS-CMP/
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├── merged_images/ # merged image pairs + metadata.csv
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└── <merged_benchmark>.json
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```
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### OPTICS-CNT
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