datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
phyground
PhyGround: Benchmarking Physical Reasoning in Generative World Models
Project page ·
Paper ·
Evaluation code ·
PhyJudge-9B
PhyGround is a criteria-grounded benchmark for diagnosing physical failures in
generated video. It contains 250 prompts covering 13 observable physical
laws across solid-body mechanics, fluid dynamics, and optics. Each prompt is
paired with a first-frame image, 10 released generation configurations, and
applicable-law labels.
The Hub repository includes:… See the full description on the dataset page: https://huggingface.co/datasets/NU-World-Model-Embodied-AI/phyground.1000-Segments-6-camera-Egocentric-Embodied-AI-Data-Sample
1000-Segments-6-camera-Egocentric-Embodied-AI-Dataset
Description
10,000-Hour Egocentric Full-Body Multimodal Dataset Purpose-built for fine-grained embodied AI manipulation training, spanning diverse real-world scenarios with high-definition stereoscopic video, full-body joint poses, and high-density semantic annotations.
For more details, please refer to the link: https://www.nexdata.ai/datasets/embodied-ai/2236?source=Huggingface
Specifications… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata-AI/1000-Segments-6-camera-Egocentric-Embodied-AI-Data-Sample.embodied-ai-ai-agent
Embodied AI Agent Meta and Traffic Dataset in AI Agent Marketplace | AI Agent Directory | AI Agent Index from DeepNLP
This dataset is collected from AI Agent Marketplace Index and Directory at http://www.deepnlp.org, which contains AI Agents's meta information such as agent's name, website, description, as well as the monthly updated Web performance metrics, including Google,Bing average search ranking positions, Github Stars, Arxiv References, etc.
The dataset is helpful for AI… See the full description on the dataset page: https://huggingface.co/datasets/DeepNLP/embodied-ai-ai-agent.