NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection

by   Yazhao Li, et al.

Due to the advantages of real-time detection and improved performance, single-shot detectors have gained great attention recently. To solve the complex scale variations, single-shot detectors make scale-aware predictions based on multiple pyramid layers. However, the features in the pyramid are not scale-aware enough, which limits the detection performance. Two common problems in single-shot detectors caused by object scale variations can be observed: (1) small objects are easily missed; (2) the salient part of a large object is sometimes detected as an object. With this observation, we propose a new Neighbor Erasing and Transferring (NET) mechanism to reconfigure the pyramid features and explore scale-aware features. In NET, a Neighbor Erasing Module (NEM) is designed to erase the salient features of large objects and emphasize the features of small objects in shallow layers. A Neighbor Transferring Module (NTM) is introduced to transfer the erased features and highlight large objects in deep layers. With this mechanism, a single-shot network called NETNet is constructed for scale-aware object detection. In addition, we propose to aggregate nearest neighboring pyramid features to enhance our NET. NETNet achieves 38.5 COCO dataset. As a result, NETNet achieves a better trade-off for real-time and accurate object detection.


page 1

page 8

page 9


Residual Bi-Fusion Feature Pyramid Network for Accurate Single-shot Object Detection

State-of-the-art (SoTA) models have improved the accuracy of object dete...

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

Many modern object detectors demonstrate outstanding performances by usi...

SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images

With the increasing demand for search and rescue, it is highly demanded ...

Leveraging Bottom-Up and Top-Down Attention for Few-Shot Object Detection

Few-shot object detection aims at detecting objects with few annotated e...

Context-aware Single-Shot Detector

SSD is one of the state-of-the-art object detection algorithms, and it c...

Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection

Recent years have witnessed many exciting achievements for object detect...

DSSD : Deconvolutional Single Shot Detector

The main contribution of this paper is an approach for introducing addit...

Please sign up or login with your details

Forgot password? Click here to reset