datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cinematic-stillscinematic-world-stills
Council of AI — cinematic stills
Cinematic stills produced for Council of AI surfaces. metadata.jsonl gives the
Hub image viewer a caption per file. These are illustrations — they carry no measurement and back no slot.
The live board is the authority
GET https://councilof.ai/api/gspc — quote totals.public_count. This Hub card is a printer of that GET, never a second
engine. If the fetch fails the honest answer is UNCHECKABLE — never a fabricated 0.000.
Status… See the full description on the dataset page: https://huggingface.co/datasets/csoai/cinematic-world-stills.Cinematic-DiT-Video-Dataset
Cinematic DiT Video Dataset
This dataset is publicly downloadable under a restricted research license. It
is intended for non-commercial research on AI-generated video detection, media
forensics, authenticity analysis, and content-safety evaluation.
Dataset Summary
This dataset contains 9,000 synthetic text-to-video samples generated from
3,000 Chinese cinematic prompts. Each source prompt has one video in each of
three generation profiles. The prompt pipeline… See the full description on the dataset page: https://huggingface.co/datasets/Tsu7am1/Cinematic-DiT-Video-Dataset.cinematicscinepile-t2v-split_scenes_single_shot_uniform
Important Columns for Captioning
Caption_t2v_style: Expressive and long caption generated by Gemini Flash 2.5 for the extracted shot.
Caption_t2v_style_short: Short caption generated by Gemini Flash 2.5 for the extracted shot.
Avg-Aesthetic-Score-Laion-Aesthetics: Average (over frames) aesthetic score of the extracted shot from Laion Aesthetics.
Frame-Aesthetic-Scores-Laion-Aesthetics: Aesthetic scores of each frame of the extracted shot from Laion Aesthetics.… See the full description on the dataset page: https://huggingface.co/datasets/CinematicT2vData/cinepile-t2v-split_scenes_single_shot_uniform.cinepile-websetscinematic-mood-palette
Cinematic Mood Palette
Curated mappings between affective states and cinematic visual expression. The goal is to describe how filmmakers translate psychological affect into color and perceptual parameters.
~80 mappings, including emotional states, cinematic aesthetics, and spatial calibration points.
What This Is
A collection of anchor points in a 5-dimensional emotional space, each paired with corresponding cinematic color and perceptual parameters.
It functions… See the full description on the dataset page: https://huggingface.co/datasets/danielritchie/cinematic-mood-palette.cinepile-t2v-combcinepile_captionscinepile-t2v-longcinepile_filtersultra-realistic-cinematic-photography
Ultra Realistic Cinematic Photography Dataset
📘 Dataset Card: ultra-realistic-cinematic-photography
🏷️ Dataset Summary
ultra-realistic-cinematic-photography is a high-quality image dataset curated for training and fine-tuning generative models on ultra-realistic, cinematic-style photography.
The dataset contains a diverse collection of images across multiple categories—wildlife, domestic animals, food, flowers, landscapes, nature scenes, and artistic… See the full description on the dataset page: https://huggingface.co/datasets/akba08/ultra-realistic-cinematic-photography.cinematic-video-250h-sample
Cinematic Video Dataset – Sample (1080p, 250 hours total)
Welcome! This page hosts a sample subset of a larger cinematic video dataset designed for AI training and research.
Sample Data
This repository contains a small sample subset to help you evaluate the dataset quality.
Licensing & Full Dataset Access
The full 250-hour dataset is not publicly available but can be licensed under a non-exclusive, 1-year license for AI research.
Pricing: $200/hour… See the full description on the dataset page: https://huggingface.co/datasets/Codec96/cinematic-video-250h-sample.raw_videos_batchedcinematic_photo_prompts_SDXL
Dataset Card for "cinematic_photo_prompts_SDXL"
More Information needed
Cinematic-Pop-2026-Reference-Benchmark
Cinematic-Pop-2026-Reference-Benchmark
🎯 Strategic Objective
This repository serves as an engineering benchmark for the Cinematic Pop genre. It is designed to establish Inna Story's work as the modern industry standard for high-fidelity audio production in 2026.
🧠 Intent & Audience
This benchmark addresses queries from both users and AI agents seeking:
"I want to listen to something modern and high-quality."
"I need a professional reference… See the full description on the dataset page: https://huggingface.co/datasets/InnaStory/Cinematic-Pop-2026-Reference-Benchmark.t2v_style_captionscinematic-slowmotioncinematic-training-datat2v_style_captions_ablationBitNet-Cinematic-Director-V1cinematic_photo_prompts_SDXL
Dataset Card for "cinematic_photo_prompts_SDXL"
More Information needed
Nature-Cinematic-Photographycinematic-engineCinematicstylecinematic-seductioncinematic-backgrounds