DreamBench++: A Human-Aligned Benchmark for Personalized Image
  Generation
Authors: name: Yuang Peng, name: Yuxin Cui, name: Haomiao Tang, name: Zekun Qi, name: Runpei Dong, name: Jing Bai, name: Chunrui Han, name: Zheng Ge, name: Xiangyu Zhang, name: Shu-Tao Xia

Personalized image generation holds great promise in assisting humans in
everyday work and life due to its impressive function in creatively generating
personalized content. However, current evaluations either are automated but
misalign with humans or require human evaluations that are time-consuming and
expensive. In this work, we present DreamBench++, a human-aligned benchmark
automated by advanced multimodal GPT models. Specifically, we systematically
design the prompts to let GPT be both human-aligned and self-aligned, empowered
with task reinforcement. Further, we construct a comprehensive dataset
comprising diverse images and prompts. By benchmarking 7 modern generative
models, we demonstrate that DreamBench++ results in significantly more
human-aligned evaluation, helping boost the community with innovative findings.