CineTechBench: cinematographic technique understanding and generation benchmark
Source: https://arxiv.org/abs/2505.15145
Repo: https://github.com/PRIS-CV/CineTechBench (last push 2025-09-19).
Structured fields
{
"checked_at": "2026-10-17T00:00:00.000Z",
"usefulness": "Expert-annotated benchmark over seven aspects (shot scale, angle, composition, camera movement, lighting, color, focal length) for both MLLM understanding and video-generation of techniques.",
"source_type": "paper",
"availability": "available",
"source_owner": "Wang et al. (BUPT, China Mobile Research Institute)",
"next_check_at": "2026-10-24T00:00:00.000Z"
}Evidence claims
- [sourced_fact] Abstract: seven aspects, over 600 annotated movie images and 120 movie clips, annotated by seasoned cinematography experts. · locator: abstract source
- [sourced_fact] Accepted to NeurIPS 2025 Datasets and Benchmarks Track (per proceedings page listing). · locator: page title source
- [sourced_fact] Companion GitHub repository PRIS-CV/CineTechBench shows no license file; README links a Hugging Face dataset. · locator: repository metadata source
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | CC-BY-NC-SA-4.0 | restricted | restricted | restricted | unknown | arXiv page lists CC BY-NC-SA 4.0 for the paper. |
| dataset | unknown | unknown | unknown | unknown | unknown | Dataset on Hugging Face; license not checked. Contains movie stills and clips, so third-party copyright likely applies. |
| code | unknown | unknown | unknown | unknown | unknown | No license file detected on the repository. |