Datasets › GIE-Bench

GIE-Bench

Introduced by Yusu Qian et al. in GIE-Bench: Towards Grounded Evaluation for Text-Guided Image Editing16 May 2025 archive 2025-07-28

GIE-Bench is a benchmark designed to evaluate text-guided image editing models across two critical dimensions:

Functional correctness — assessed via VQA-style multiple-choice questions Content preservation — evaluated through object-aware masking and image similarity It includes over 1,000 high-quality editing examples across 20 categories and 9 edit types, with masks, instructions, and questions.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

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Variants archive 2025-07-28

  • GIE-Bench

1 variant name, as the archive lists them.

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