UNBIASED LOOK AT DATASET BIAS Antonia Torralba Alexei A. Efros MIT CMU Presented by: Vivek Dubey Harika Sabbella NAMING DATASETS 1) Caltech-101 2) UIUC 3) MSRC 4) Tiny Images 5) ImageNet 6) PASCAL VOC 7) LabelMeS 8) SUN-09 9) 15 Scenes 10) Corel 11) Caltech-256 12) COIL-100 ARE CURRENT DATASETS BIASED? ! Randomly sampled 1000 images from training images for the 12 datasets and trained a 12-way linear SVM classifier ! Tested classifier on 300 random images from the test images of the 12 datasets RESULTS OF “NAME THAT DATASET” CLASSIFIER CONFUSION MATRIX TRAINING THE “CARS” CLASSIFIER ! Applied classifier to object crops of cars from five datasets ! Classifier was still able to tell the datasets apart (61% performance) OUTLINE Step 1) Understanding how bias sneaks into our datasets Step 2) Raise awareness in the visual recognition commu
