What makes for effective detection proposals?

Understand

Current top performing object detectors employ detection proposals to guide the search for objects, thereby avoiding exhaustive sliding window search across images.

• Despite the popularity and widespread use of detection proposals, it is unclear which trade-offs are made when using them during object detection.
• We provide an in-depth analysis of twelve proposal methods along with four baselines regarding proposal repeatability, ground truth annotation recall on PASCAL, ImageNet, and MS COCO, and their impact on DPM, R-CNN, and Fast R-CNN detection performance.
• Our analysis shows that for object detection improving proposal localisation accuracy is as important as improving recall.