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license: apache-2.0 |
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# Circular-based Relation Probing Evaluation (CRPE) |
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CRPE is a benchmark designed to quantitatively evaluate the object recognition and relation comprehension ability of models. |
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The evaluation is formulated as single-choice questions. |
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The benchmark consists of four splits: |
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**Existence**, **Subject**, **Predicate**, and **Object**. |
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The **Existence** split evaluates the object recognition ability while the remaining splits are designed to evaluate the capability of relation comprehension, focusing on probing each of the elements in the relation triplets `(subject, predicate, object)` separately. |
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Some data examples are shown below. |
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<img width="800" alt="image" src="https://cdn-uploads.huggingface.co/production/uploads/619507e7b74b6c591f794340/_NKaowl2OUBAjck1XCAPm.jpeg"> |
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Additionally, to evaluate the dependency on language priors, we also include abnormal data in our evaluation. |
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These images in these abnormal data depict relation triplets that are very rare in the real world. |
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<img width="800" alt="image" src="https://cdn-uploads.huggingface.co/production/uploads/619507e7b74b6c591f794340/qKWw7Qb93OXClxI_VrCRk.jpeg"> |
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For a robust evaluation, we adopt CircularEval as our evaluation strategy. |
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Under this setting, a question is considered as correctly answered only when the model consistently predicts the correct answer in each of the N iterations, with N corresponding to the number of choices. |
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In each iteration, a circular shift is applied to both the choices and the answer to form a new query for the model. |
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See our [project](https://github.com/OpenGVLab/all-seeing/all-seeing-v2) to learn more details! |
