impression
first-impressions-v2
Dataset Card for First Impressions V2
The first impressions data set, comprises 10000 clips (average duration 15s) extracted from more than 3,000 different YouTube high-definition (HD) videos of people facing and speaking in English to a camera. The videos are split into training, validation and test sets with a 3:1:1 ratio. People in videos show different gender, age, nationality, and ethnicity.
Videos are labeled with personality traits variables. Amazon Mechanical Turk (AMT) was… See the full description on the dataset page: https://huggingface.co/datasets/yeray142/first-impressions-v2.first-impressions-v3impressionist_imgopenbrush-impressionism
OpenBrush Impressionism
Every Impressionist work from OpenBrush-75K — the largest movement subset.
Curated subset of jaddai/openbrush. Same CC0 license, same caption schema, same VLM (Qwen3-VL-30B-A3B). This subset exists so you don't have to download 75,313 images to get to the 12,798 you actually want.
Why this subset
Broad-coverage subset for training on the Impressionist visual language: broken brushwork, light-on-color theory, plein-air staging, atmospheric… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush-impressionism.openbrush-impressionist-landscapes
OpenBrush Impressionist Landscapes
Cross-cut subset: Impressionist landscape paintings from OpenBrush-75K. The most-targeted style+genre combination for Impressionist landscape LoRA training.
Curated subset of jaddai/openbrush. Same CC0 license, same caption schema, same VLM (Qwen3-VL-30B-A3B). This subset exists so you don't have to download 75,313 images to get to the 4,308 you actually want.
Why this subset
The intersection of the largest movement… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush-impressionist-landscapes.Impressions
Dataset Card for "Impressions"
Overview
The Impressions dataset is a multimodal benchmark that consists of 4,100 unique annotations and over 1,375 image-caption pairs from the photography domain. Each annotation explores (1) the aesthetic impactfulness of a photograph, (2) image descriptions in which pragmatic inferences are welcome, (3) emotions/thoughts/beliefs that the photograph may inspire, and (4) the aesthetic elements that elicited the expressed impression.
EMNLP… See the full description on the dataset page: https://huggingface.co/datasets/SALT-NLP/Impressions.