FoveaBox: Beyound Anchor-Based Object Detection

We present FoveaBox, an accurate, flexible, and completely anchor-free framework for object detection. While almost all state-of-the-art object detectors utilize predefined anchors to enumerate possible locations, scales and aspect ratios for the search of the objects, their performance and generalization ability are also limited to the design of anchors. Instead, FoveaBox directly learns the object existing possibility and the bounding box coordinates without anchor reference. This is achieved by: (a) predicting category-sensitive semantic maps for the object existing possibility, and (b) producing category-agnostic bounding box for each position that potentially contains an object. The scales of target boxes…

• NS
  National Science Foundation
• DF
  Deutsche Forschungsgemeinschaft

  Awards: 61621136008, DFG TRR-169, 91848206, TRR-169, U1613212
• NN
  National Natural Science Foundation of China

  Awards: 61621136008, 91848206, TRR-169, U1613212