ICE-Bench (ICE = Image Creating and Editing) is a unified, multi-task benchmark for evaluating image generation and image editing models. Introduced in the paper “ICE-Bench: A Unified and Comprehensive Benchmark for Image Creating and Editing” (arXiv:2503.14482), it decomposes image creation/editing into four coarse categories (no-reference / reference × creating / editing) and further into 31 fine-grained tasks (Task 1–31). The benchmark uses a multi-dimensional evaluation protocol spanning 6 evaluation dimensions and 11 automatic metrics that measure imaging quality, prompt following, source consistency, reference consistency, controllability, and aesthetics. The authors provide benchmark code to compute per-task scores and an overall “Task1-31” aggregate score; the dataset and automated evaluation code are released (MIT license) on Hugging Face (ali-vilab/ICE-Bench).
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