An Extensive Benchmark for Single-round and Multi-round Instruction-based Image Editing
In recent years, there have been notable advancements in the area of instruction-based image editing (IIE), which focuses on the automatic alteration of input images using a model. Nevertheless, assessing the effectiveness of these editing models poses a considerable challenge due to the intricate nature of instructions and the wide variety of edits. To tackle this problem, one urgent task in this domain is the development of a robust evaluation framework that can precisely gauge the quality of editing outcomes and offer valuable benchmarks to guide future improvements. To address this challenge, we present a comprehensive evaluation benchmark named I2EBench2.0, designed for single-round ...
| Authors | Yiwei Ma, Ke Ye, Weihuang Lin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 14 June 2026 |
| Last updated at source | 14 June 2026 |
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