Hanfu-Bench: A Multimodal Benchmark on Cross-Temporal Cultural
  Understanding and Transcreation
Culture is a rich and dynamic domain that evolves across both geography and
time. However, existing studies on cultural understanding with vision-language
models (VLMs) primarily emphasize geographic diversity, often overlooking the
critical temporal dimensions. To bridge this gap, we introduce Hanfu-Bench, a
novel, expert-curated multimodal dataset. Hanfu, a traditional garment spanning
ancient Chinese dynasties, serves as a representative cultural heritage that
reflects the profound temporal aspects of Chinese culture while remaining
highly popular in Chinese contemporary society. Hanfu-Bench comprises two core
tasks: cultural visual understanding and cultural image transcreation.The
former task examines temporal-cultural feature recognition based on single- or
multi-image inputs through multiple-choice visual question answering, while the
latter focuses on transforming traditional attire into modern designs through
cultural element inheritance and modern context adaptation. Our evaluation
shows that closed VLMs perform comparably to non-experts on visual cutural
understanding but fall short by 10\% to human experts, while open VLMs lags
further behind non-experts. For the transcreation task, multi-faceted human
evaluation indicates that the best-performing model achieves a success rate of
only 42\%. Our benchmark provides an essential testbed, revealing significant
challenges in this new direction of temporal cultural understanding and
creative adaptation.
684009f8a33aeee1125b5765
Li Zhou
claimed_verified
2025-06-07T05:49:28.567Z
63d925b189a9683b46d33e89
https://cdn-avatars.huggingface.co/v1/production/uploads/63d925b189a9683b46d33e89/lYFvL-rLytMVaWVlfGkL_.jpeg
Li Zhou
user
lizhou21
684009f8a33aeee1125b5766
Lutong Yu
684009f8a33aeee1125b5767
Dongchu Xie
684009f8a33aeee1125b5768
Shaohuan Cheng
684009f8a33aeee1125b5769
Wenyan Li
admin_assigned
2025-06-05T07:36:16.451Z
619b506f70d03780cbec5806
/avatars/ea2b0b8f0a3eb16d53ef40da9981c397.svg
wenyan li
user
lyan62
684009f8a33aeee1125b576a
Haizhou Li
Hanfu-Bench: A Multimodal Benchmark on Cross-Temporal Cultural
  Understanding and Transcreation
Culture is a rich and dynamic domain that evolves across both geography and
time. However, existing studies on cultural understanding with vision-language
models (VLMs) primarily emphasize geographic diversity, often overlooking the
critical temporal dimensions. To bridge this gap, we introduce Hanfu-Bench, a
novel, expert-curated multimodal dataset. Hanfu, a traditional garment spanning
ancient Chinese dynasties, serves as a representative cultural heritage that
reflects the profound temporal aspects of Chinese culture while remaining
highly popular in Chinese contemporary society. Hanfu-Bench comprises two core
tasks: cultural visual understanding and cultural image transcreation.The
former task examines temporal-cultural feature recognition based on single- or
multi-image inputs through multiple-choice visual question answering, while the
latter focuses on transforming traditional attire into modern designs through
cultural element inheritance and modern context adaptation. Our evaluation
shows that closed VLMs perform comparably to non-experts on visual cutural
understanding but fall short by 10\% to human experts, while open VLMs lags
further behind non-experts. For the transcreation task, multi-faceted human
evaluation indicates that the best-performing model achieves a success rate of
only 42\%. Our benchmark provides an essential testbed, revealing significant
challenges in this new direction of temporal cultural understanding and
creative adaptation.
Hanfu-Bench, a new expert-curated dataset, addresses temporal aspects of cultural understanding and creative adaptation using vision-language models, highlighting significant challenges in these tasks.
vision-language models multimodal dataset cultural visual understanding cultural image transcreation visual question answering cultural element inheritance modern context adaptation