Indoor 67 Heatmaps: Confident Errors
Heatmaps for the most confident errors in the indoor67 dataset. The heatmaps were generated entirely automatically, and show which pixels contributed most to the classification of the image. Click on the heatmaps to see the actual elements that had the most influence on the classification. Note that in the paper the SVM uses a max pooling step, and therefore the heatmaps shown there only highlight the maximal deteciton for a given element within a given region (since that's the only detection that contributes to the SVM score), and hence they appear sparse, especially in texutred regions. In these heatmaps, however, we blend all detections, which looks considerably better even if it's not quite as useful for debugging the SVM performance.
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