metadata

dataset_info:
  features:
    - name: prompt
      dtype: string
    - name: prompt_asset
      dtype: image
    - name: video1
      dtype: string
    - name: video2
      dtype: string
    - name: weighted_results1_Alignment
      dtype: float32
    - name: weighted_results2_Alignment
      dtype: float32
    - name: detailedResults_Alignment
      list: string
    - name: weighted_results1_Coherence
      dtype: float32
    - name: weighted_results2_Coherence
      dtype: float32
    - name: detailedResults_Coherence
      list: string
    - name: weighted_results1_Preference
      dtype: float32
    - name: weighted_results2_Preference
      dtype: float32
    - name: detailedResults_Preference
      list: string
    - name: file_name1
      dtype: string
    - name: file_name2
      dtype: string
    - name: model1
      dtype: string
    - name: model2
      dtype: string
  splits:
    - name: train
      num_bytes: 318051385
      num_examples: 198
  download_size: 161801984
  dataset_size: 318051385
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: apache-2.0
task_categories:
  - video-classification
  - text-to-video
  - text-classification
language:
  - en
tags:
  - videos
  - i2v
  - image-2-video
  - image2video
  - image-to-video
  - human
  - annotations
  - preferences
  - likert
  - coherence
  - alignment
  - style
  - seedance
  - seedance-1
  - seedance-1-pro
pretty_name: seedance-1-pro Human Preferences
size_categories:
  - 1K<n<10K

Rapidata Video Generation Hailuo-02 v Marey Human Preference

In this dataset, ~6k human responses from ~2k human annotators were collected to evaluate Seedance 1 Pro video generation model on our benchmark. This dataset was collected in roughtly 5 min using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.

Explore our latest model rankings on our website.

If you get value from this dataset and would like to see more in the future, please consider liking it ❤️

To add your own model to the benchmark send us an e-mail at: [email protected]

Overview

Explanation of the colums

The dataset contains paired video comparisons. Each entry includes 'video1' and 'video2' fields, which contain links to downscaled GIFs for easy viewing. The full-resolution videos can be found here

The weighted_results column contains scores ranging from 0 to 1, representing aggregated user responses. Individual user responses can be found in the detailedResults column.

Alignment

The alignment score quantifies how well an video matches its prompt. Users were asked: "Which video fits the description better?".

Examples

The calf moves forward, gently munching on the hay scattered on the ground.

Seedance 1 Pro

(Score: 90.61%)

Hailuo-02

(Score: 9.39%)

The fern slowly unfurls as a gentle breeze causes it to sway softly.

Seedance 1 Pro

(Score: 15.68%)

Hailuo-02

(Score: 84.32%)

Coherence

The coherence score measures whether the generated video is logically consistent and free from artifacts or visual glitches. Without seeing the original prompt, users were asked: "Which video has more glitches and is more likely to be AI generated?"

Examples

Seedance 1 Pro

(Glitch Rating: 8.78%)

Marey

(Glitch Rating: 91.22%)

Seedance 1 Pro

(Glitch Rating: 80%)

Hailuo-02

(Glitch Rating: 20%)

Preference

The preference score reflects how visually appealing participants found each video, independent of the prompt. Users were asked: "Which video do you prefer aesthetically?"

Examples

Seedance 1 Pro

(Score: 90.74%)

Marey

(Score: 9.26%)

Seedance 1 Pro

(Score: 9.03%)

Hailuo-02

(Score: 90.97%)

About Rapidata

Rapidata's technology makes collecting human feedback at scale faster and more accessible than ever before. Visit rapidata.ai to learn more about how we're revolutionizing human feedback collection for AI development.

Other Datasets

We run a benchmark of the major video generation models, the results can be found on our website. We rank the models according to their coherence/plausiblity, their aligment with the given prompt and style prefernce. The underlying 2M+ annotations can be found here:

Link to the Rich Video Annotation dataset
Link to the Coherence dataset
Link to the Text-2-Image Alignment dataset
Link to the Preference dataset