datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DL3DV-Evaluation
DL3DV Testing Split Download Instructions
This repo contains all 55 scenes for evaluation. Note: it is an independent dataset, and none of its scenes overlap with those in DL3DV-10K. Have a galance on the preview page: https://dl3dv-10k.github.io/DL3DV-Testing-Split-Preview/.
Download
As the whole benchmark dataset is ~500G, a python script to download and untar files.
Environment Setup
The download script relies on huggingface hub, tqdm. You can download by… See the full description on the dataset page: https://huggingface.co/datasets/DL3DV/DL3DV-Evaluation.Semi-Truths-Evalset
Semi-Truths: The Evaluation Sample
Recent efforts have developed AI-generated image detectors claiming robustness against various augmentations, but their effectiveness remains unclear. Can these systems detect varying degrees of augmentation?
To address these questions, we introduce Semi-Truths, featuring 27,600 real images, 245,300 masks, and 850,200 AI-augmented images featuring varying degrees of targeted and localized edits, created using diverse augmentation methods… See the full description on the dataset page: https://huggingface.co/datasets/semi-truths/Semi-Truths-Evalset.BridgeVLA_COLOSSEUM_EVAL_DATAarxiv: https://arxiv.org/abs/2506.07961
PixArt-Eval-30KDA-2-Evaluation
DA2: Depth Anything in Any Direction
DA2 predicts dense, scale-invariant distance from a single 360° panorama in an end-to-end manner, with remarkable geometric fidelity and strong zero-shot generalization.
🎮 Usage
Please see here.
🎓 Citation
If you find these datasets useful, please consider citing 🌹:
@article{li2025depth,
title={DA$^{2}$: Depth Anything in Any Direction},
author={Li, Haodong and Zheng, Wangguangdong and He, Jing and Liu, Yuhao and… See the full description on the dataset page: https://huggingface.co/datasets/haodongli/DA-2-Evaluation.BridgeVLA_RLBench_EVAL_DATAarxiv: https://arxiv.org/abs/2506.07961
Offline_Evaluationcls-evaluation-datasetobject_images
Overview
This dataset contains 2D rendered images generated from 3D assets originally sourced from Objaverse and Objathor.The purpose of this dataset is to provide a large-scale collection of photo-realistic renderings for research on vision, multimodal learning, and text-to-3D understanding.
Following prior works such as Diffusion4D and Stable-Zero123,we release only the rendered 2D images (not the original 3D assets) to facilitate efficient experimentation while preserving the… See the full description on the dataset page: https://huggingface.co/datasets/LEGO-Eval/object_images.see-2-sound-evalWe sample images from Laion400M and the web to construct this small evaluation set.
ori_coco_evalrelo_coco_evalOffline_Evaluationeval_benchmark_vlm_halluGaussianAnything-evalworldarena_832_480_and_abot_eval_ESRGAN.tarhdm_ccip_eval_images