Image Data

I1 - Yahoo! Flickr Creative Common Images tagged with ten concepts, version 1.0

This dataset contains a list of Creative Commons licensed images from Flickr and features computed on the images.

I2 - Yahoo! Shopping Shoes Image Content, version 1.0 (131 MB)

The main purpose of releasing this dataset is to provide a new benchmark for the problem of fine grained object recognition using shoe as an example. Most of the existing datasets in the research community can be used to develop algorithms to classify coarse level objects, e.g. is this a dog or cat. But in reality, sometimes we need to do fine grained object recognition, e.g. is this a German Shepherd or Chiwawa? Our Shoe dataset provides a new benchmark which contains a diverse collection of types of shoe photos. Object recognition algorithms aim to identify if there is a pair of shoe and the type of shoes (clogs or high heels) appear in a photo automatically. Yahoo! Shopping is the best place to read user reviews, explore great products and buy online. We collect a small subset of product from Yahoo! Shopping to reflect the interesting real-world problem of fine-grained object recognition. We hope that releasing this dataset helps the academic machine learning and computer vision researchers to come up with more accurate object recognition algorithms. This dataset contains a small sample of the Yahoo! Shopping shoe photos. This dataset contains 107 folders, each corresponding to a type and brand of shoe.Also included is a .mat file (shoe_annos.mat), which contains a bounding box for each shoe image. The dataset may be used by researchers to validate image classification systems for research purpose.

I3 - Yahoo Flickr Creative Commons 100M (14G) (Hosted on AWS)

This dataset contains a list of photos and videos. This list is compiled from data available on Yahoo! Flickr. All the photos and videos provided in the list are licensed under one of the Creative Commons copyright licenses, and as such they can be used for benchmarking purposes as long as the photographer/videographer is credited for the original creation.

If you decide to use the YFCC100M dataset in your work, please cite the following paper: B. Thomee, D.A. Shamma, G. Friedland, B. Elizalde, K. Ni, D. Poland, D. Borth, L. Li, "YFCC100M: The New Data in Multimedia Research", Communications of the ACM, 59(2), pp. 64-73, 2016.

This dataset is hosted on the Amazon Web Services platform, which requires a free Amazon Web Services login for access.

Here are all the papers published on this Webscope Dataset:

I4 - Title-based Video Summarization dataset, version 1.1(644M)

The TVSum50 dataset contains 50 videos and their shot-level importance scores obtained via crowdsourcing. The 50 videos, collected from YouTube?, comes with the Creative Commons CC-BY (v3.0) license. We release both the video files and their URLs. The shot-level importance scores are annotated by crowd-workers and contain 20 annotations per video. This dataset may serve as a benchmark to validate video summarization techniques.

I5 - Yahoo Flickr mobile photo filters, vision tags and engagement metrics, Version 1.0

This dataset contains a small sample of Flickr mobile photo meta data. These photos were uploaded through Flickr or Instagram on Flickr mobile app and some of them were filtered by the user prior to upload. The dataset contains the information on whether the photo was filtered, the vision tags associated with the photo and engagement metrics on the photo. The dataset may be used by researchers to validate impacts of filters and vision tags on engagement.