%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Livefood
Overview :
LiveFood is a dataset consisting of over 5100 gourmet videos, encompassing the four domains of ingredients, cooking, presentation, and consumption. All videos are meticulously annotated by professionals, and a strict double-checking system is employed to further ensure the quality of annotations. We have also proposed the Global Prototype Encoding (GPE) model to address the incremental learning problem, which achieves competitive performance compared to traditional techniques.
Target Users :
["Video Highlight Detection","Incremental Learning"]
Use Cases
Training a video highlight detection model using the LiveFood dataset
Conducting domain incremental learning experiments based on the four domains of data from LiveFood
Using the abundant annotations in LiveFood for video understanding research
Features
Contains over 5100 finely annotated gourmet videos
Covers the four domains of ingredients, cooking, presentation, and consumption
High-quality video annotations
Global Prototype Encoding (GPE) model
Featured AI Tools
Celebv Text
CelebV-Text is a large-scale, high-quality, and diverse face text-video dataset designed to promote research on face text-video generation tasks. The dataset contains 70,000 out-door face video clips, each accompanied by 20 text descriptions covering 40 general appearances, 5 detailed appearances, 6 lighting conditions, 37 actions, 8 emotions and 6 light directions. CelebV-Text has been validated through comprehensive statistical analysis for its superiority in video, text, and text-video correlation, and it constructs a benchmark to standardize the evaluation of face text-video generation tasks.
AI Datasets
85.0K
Livefood
LiveFood is a dataset consisting of over 5100 gourmet videos, encompassing the four domains of ingredients, cooking, presentation, and consumption. All videos are meticulously annotated by professionals, and a strict double-checking system is employed to further ensure the quality of annotations. We have also proposed the Global Prototype Encoding (GPE) model to address the incremental learning problem, which achieves competitive performance compared to traditional techniques.
AI Datasets
67.1K