Intro CALTECH 256 Greg Griffin, Alex Holub and

Intro CALTECH 256 Greg Griffin, Alex Holub and

Intro CALTECH 256 Greg Griffin, Alex Holub and Pietro Perona Overview 256 Object Categories + Clutter At least 80 images per category 30608 images instead of 9144

Caltech-101: Drawbacks Smallest category size is 31 images: Too easy? left-right aligned Rotation artifacts

Soon will saturate performance N train 30 Caltech-256 : New Features Smallest category size now 80 images Harder Not left-right aligned No artifacts

Performance is halved More categories New and larger clutter category Category Sizes 101 clutter 256 clutter

Collection Procedure Similar to Caltech-101 (Li, Fergus, Perona) Four sorters rate the images

1. good: a clear example 2. bad: confusing, occluded, cluttered, or artistic 3. not applicable: object category not present 92,652 Images from Google and Picsearch 32.1% were rated good and kept

Some images borrowed from 29 of the largest Caltech-101 categories (green) Taxonomy Taxonomy (zoom)

Recall Diminishing returns from Google Images Test for Antonio Torralba Try to find: blimp, clutter, grasshopper, picnic-table, refrigerator, watermelon Test for Antonio Torralba

watermelon refrigerator grasshopper picnic-table blimp

clutter Localization? watermelon refrigerator grasshopper

Caltech-101/256 are not recommended for object localization tests picnic-table blimp clutter

Benchmarks Expect roughly half the 101 performance Clutter: 827 Background Images Stephen Shore, Uncommon Places

Acknowledgements Rob Fergus and Fei Fei Li, Pierre Moreels for code and procedures developed for the Caltech-101 image set Marco Ranzato and Claudio Fanti for miscellaneous help Sorters: Lis Fano, Nick Lo, Julie May, Weiyu Xu for making this image set possible with

their hard work Download: http://vision.caltech.edu/Image_Datasets/Caltech256

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