aryashah00/CatVision
CatVision: Human–Cat Vision Frame Pairs Official dataset for the paper: Purrturbed but Stable: Human-Cat Invariant Representations Across CNNs, ViTs and Self-Supervised ViTsArya Shah et al. · arXiv:2511.02404 This dataset contains 346,400 paired video frames rendered under human vision and simulated cat vision optics. It was used to benchmark cross-species representational alignment across CNNs, supervised ViTs, windowed transformers, and self-supervised ViTs (DINO) using CKA… See the full description on the dataset page: https://huggingface.co/datasets/aryashah00/CatVision.
CatVision: Human–Cat Vision Frame Pairs
Official dataset for the paper:
Purrturbed but Stable: Human-Cat Invariant Representations Across CNNs, ViTs and Self-Supervised ViTs Arya Shah et al. · arXiv:2511.02404
This dataset contains 346,400 paired video frames rendered under human vision and simulated cat vision optics. It was used to benchmark cross-species representational alignment across CNNs, supervised ViTs, windowed transformers, and self-supervised ViTs (DINO) using CKA and RSA.
Dataset Structure
Statistics
Usage
from datasets import load_dataset
ds = load_dataset("aryashah00/CatVision")
sample = ds["train"][0]
# Access images (returned as PIL.Image)
human_img = sample["human_frame"]
cat_img = sample["cat_frame"]Citation
@misc{shah2024purrturbed,
title = {Purrturbed but Stable: Human-Cat Invariant Representations
Across CNNs, ViTs and Self-Supervised ViTs},
author = {Arya Shah and others},
year = {2024},
eprint = {2511.02404},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2511.02404}
}License
Released under CC BY 4.0.