multi-human
multilingual-ai-human-detector_xlm-roberta-base_Spydaz_Web_LCARS_Artificial_Human_R1_002-Multi-lingual-GGUF_Spydaz_Web_LCARS_Artificial_Human_R1_002-Multi-lingual-Thinking-GGUFnucleotide-transformer-v2-50m-multi-species-finetuned-human-enhancers-cohnsplicebert-human.510borzoi-humandeltasplice-humancrypto-destroy-all-humans-multiple-models
MultiHumanCarRacing
MultiHumanCarRacing
Documentation: https://github.com/NaOH12/RacingSentimentAnalysis
(meta_data folder is not available since it is being flagged as unsafe. This can be generated/modified with sample_builder.py)
Dataset and code are free to use. Please consider reaching out if you are hiring! 😊
RenderMatte-Human-Multi-Street-2K
RenderMatte Human Multi-Person Street 2K
A synthetic video-matting dataset for the multi-person case. Two or three rigged 3D human characters are
animated and rendered together in one Blender (Cycles) scene, then composited onto real street footage.
Every frame comes with its 16-bit alpha matte.
It is built on top of the single-person VideoMatting pipeline and its source-asset collection, and keeps the
same render and compositing settings wherever possible.
Research use only.… See the full description on the dataset page: https://huggingface.co/datasets/Deanshy1/RenderMatte-Human-Multi-Street-2K.Cabin-multi-modal-recognition-dataset-of-human
XAILab-CyberSpark/Cabin-multi-modal-recognition-dataset-of-human
由XAI Lab 汽车智能座舱数据集生成引擎生成的座舱垂域任务数据集，面向智能座舱舱内识人场景，本次开源demo数据集包含719张图像及标签，涵盖不同性别、年龄、情绪（表情）、行为动作、衣物等的标签，可用于舱内多模态感知模型SFT训练。
The cockpit vertical domain task dataset generated by the XAI Lab vehicle intelligent cockpit dataset generation engine is oriented to the intelligent cockpit human recognition scene. The Open Source demo dataset contains 719 images and tags, labels covering different genders, ages, emotions… See the full description on the dataset page: https://huggingface.co/datasets/OpenSparX/Cabin-multi-modal-recognition-dataset-of-human.multi_domain_ai_human_text
multi_domain_ai_human_text — Datasheet
Balanced, multi-domain AI-vs-human text detection benchmark with dedicated
out-of-distribution and adversarial evaluation panels. Built by
scripts/build_paper_dataset.py from an 11-corpus unified aggregation.
Splits
Split
AI
Human
Total
Purpose
train
300,000
300,000
600,000
training (balanced, English, clean)
validation
2,996
2,999
5,995
model selection
test
4,991
4,999
9,990
in-distribution test… See the full description on the dataset page: https://huggingface.co/datasets/acmc/multi_domain_ai_human_text.humaneval_multi
humaneval_multi — evaluation data (OpenCompass format)
Bud Ecosystem eval mirror (config humaneval_multi_gen). Source nuprl/MultiPL-E — license MIT, unchanged; all rights remain with the original authors.
multi-humanevalThis dataset contains a viewer-friendly version of the dataset at mxeval/multi-humaneval with language-specific stop tokens added in. It is made available separately for the convenience of the vllm-code-harness package.