Datasets:
image imagewidth (px) 144 4.11k | label class label 5
classes |
|---|---|
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
01-cartoon | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game | |
12-game |
Gen-Arena
Gen-Arena is a text-to-image evaluation benchmark for compositional prompt following and reference-conditioned generation. Each sample contains a natural-language generation prompt, optional reference images, named entities, and fine-grained constraints.
Gen-Arena is introduced in the paper SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation as a human-annotated benchmark with entity- and constraint-level specifications.
This package contains 300 samples across 6 categories:
| Category | Samples | Unique image files | Reference slots |
|---|---|---|---|
1-cartoon |
50 | 56 | 56 |
2-game |
50 | 103 | 104 |
3-sports |
50 | 50 | 50 |
4-entertainment |
50 | 50 | 50 |
5-competition |
50 | 0 | 0 |
6-ceremony |
50 | 30 | 50 |
Files
data/gen_arena.jsonl: unified metadata file with all 300 samples.reference_images/<category>/: reference images grouped by category.
All image paths in data/gen_arena.jsonl are root-relative paths.
Schema
Each row in data/gen_arena.jsonl has the following fields:
id: unique sample id.category: category directory name.prompt: generation prompt.reference_images: list of objects withidand root-relativepath.reference_image_paths: list of root-relative image paths.num_reference_images: number of reference images for the sample.entities: list of named entities and optional reference links.constraints: list of fine-grained constraints withid,type,text, anddepends_on.num_entities: entity count.num_constraints: constraint count.constraint_type_counts: counts by constraint type.
Constraint types are attribute, layout, and relation.
Loading
from datasets import load_dataset
dataset = load_dataset("json", data_files="data/gen_arena.jsonl", split="train")
print(dataset[0]["prompt"])
print(dataset[0]["reference_image_paths"])
Reference images can be loaded by joining each reference_image_paths value with the dataset root. For example, image paths follow the form reference_images/1-cartoon/1-cartoon_001_Tiggy.jpg.
Notes
5-competitionis intentionally text-only and has no reference images.- Some samples share the same reference image file after exact duplicate cleanup.
- The license and redistribution status of reference images should be verified before public release.
Citation
Citation information will be added after the associated paper is publicly available.
- Downloads last month
- 17