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Rolling hills under the moonlight under clear skies, featuring with crystal-clear waters adorned with a lone wolf.
Desert oasis at sunset in the midst of a thunderstorm, featuring with fields of wildflowers adorned with a lone wolf.
Rolling hills under the moonlight under clear skies, featuring with towering trees adorned with a family of deer.
Tranquil lake under the midday sun surrounded by mist and fog, featuring with rugged terrain adorned with birds in flight.
Lush forest under the midday sun under a colorful rainbow, featuring with golden sand dunes adorned with a playful pod of dolphins.
Lush forest under the midday sun surrounded by mist and fog, featuring with a cascading waterfall adorned with colorful butterflies.
Tranquil lake at dawn under a colorful rainbow, featuring with fields of wildflowers adorned with colorful butterflies.
Majestic mountains under the moonlight under clear skies, featuring with rugged terrain adorned with a family of deer.
Lush forest at dawn surrounded by mist and fog, featuring with golden sand dunes adorned with colorful butterflies.
Lush forest under the midday sun under clear skies, featuring with crystal-clear waters adorned with colorful butterflies.

GenEx-DB-Panorama-World 🎞️🌍

This is the GenEx-DB panorama dataset for world initialization.

The dataset contains 120,000 panorama images generated by Flux-Dev-Panorama-LoRA-2, the prompts are from ``.

Each row is pairs with its generation prompt and extracted front view image from the panorama.

The dataset has been split into train, validation, test at 100,000, 10,000, 10,000.

πŸš€ Usage

from datasets import load_dataset

# Login using e.g. `huggingface-cli login` to access this dataset
ds = load_dataset("genex-world/GenEx-DB-Panorama-World", streaming=True)

# Inspect one example
for row in ds:
    print(row['prompt'])
    print(row['panorama'])
    print(row['front_view'])
    break

✨ BibTex

@misc{lu2025genexgeneratingexplorableworld,
      title={GenEx: Generating an Explorable World}, 
      author={Taiming Lu and Tianmin Shu and Junfei Xiao and Luoxin Ye and Jiahao Wang and Cheng Peng and Chen Wei and Daniel Khashabi and Rama Chellappa and Alan Yuille and Jieneng Chen},
      year={2025},
      eprint={2412.09624},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.09624}, 
}
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