datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IGF-Bench
IGF-Bench: Indoor Geometric Fidelity Benchmark
Anonymous mirror for NeurIPS 2026 Evaluations and Datasets Track double-blind review.
The de-anonymised author/maintainer information will replace this header at camera-ready.
IGF-Bench is the first benchmark for evaluating structural-level geometric fidelity of conditionally generated indoor scene images, going beyond perceptual metrics like FID and LPIPS. It pairs 3,600 calibrated synthetic ground-truth views with 21,600 generated… See the full description on the dataset page: https://huggingface.co/datasets/igfbench-neurips2026/IGF-Bench.visual_ai_at_neurips2025_jina
Dataset Card for Voxel51/visual_ai_at_neurips2025
This is a FiftyOne dataset with 1134 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("harpreetsahota/visual_ai_at_neurips2025_jina")
# Launch the App
session =… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/visual_ai_at_neurips2025_jina.visual_ai_at_neurips2025_nomic
Dataset Card for Voxel51/visual_ai_at_neurips2025
This is a FiftyOne dataset with 1134 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("harpreetsahota/visual_ai_at_neurips2025_nomic")
# Launch the App
session =… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/visual_ai_at_neurips2025_nomic.