NMS Survery
define the problem: (1) single class(pedestrian) or multi-class? single(pedestrian) (2) in Mask-RCNN(Faster-RCNN), NMS be applied in both training and inference, our target just replaces the inference part or both parts? inference (3) at the moment, are we mainly focus on the single image or video frames? single image (4) are we just focus on detection or both detection and segmentation? detection, but need to use segmentation to help detection. (5) shall we use tight_boxes or lose_boxes as gt_annots? (which make difference for gt_masks) related papers: cat1: pairwise(clustering) 1. Non-maximum suppression for object detection by passing messages between windows_Rasmus Rothe_ACCV2014 https://www.vision.ee.ethz.ch/publications/papers/proceedings/eth_biwi_01126.pdf based on Affinity propagation clustering(APC), using a Latent Structured SVM(LSSVM) to learn the weigh...