Feature-Fused SSD: Fast Detection for Small Objects

09/15/2017
by   Guimei Cao, et al.
0

Small objects detection is a challenging task in computer vision due to its limited resolution and information. In order to solve this problem, the majority of existing methods sacrifice speed for improvement in accuracy. In this paper, we aim to detect small objects at a fast speed, using the best object detector Single Shot Multibox Detector (SSD) with respect to accuracy-vs-speed trade-off as base architecture. We propose a multi-level feature fusion method for introducing contextual information in SSD, in order to improve the accuracy for small objects. In detailed fusion operation, we design two feature fusion modules, concatenation module and element-sum module, different in the way of adding contextual information. Experimental results show that these two fusion modules obtain higher mAP on PASCALVOC2007 than baseline SSD by 1.6 and 1.7 points respectively, especially with 2-3 points improvement on some smallobjects categories. The testing speed of them is 43 and 40 FPS respectively, superior to the state of the art Deconvolutional single shot detector (DSSD) by 29.4 and 26.4 FPS. Keywords: small object detection, feature fusion, real-time, single shot multi-box detector

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 3

page 6

page 7

12/04/2017

FSSD: Feature Fusion Single Shot Multibox Detector

SSD (Single Shot Multibox Detetor) is one of the best object detection a...
04/12/2020

MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

In this paper, we address the 3D object detection task by capturing mult...
11/16/2018

Detecting The Objects on The Road Using Modular Lightweight Network

This paper presents a modular lightweight network model for road objects...
05/07/2020

Seismic Shot Gather Noise Localization Using a Multi-Scale Feature-Fusion-Based Neural Network

Deep learning-based models, such as convolutional neural networks, have ...
05/05/2021

Towards an efficient framework for Data Extraction from Chart Images

In this paper, we fill the research gap by adopting state-of-the-art com...
07/23/2018

Dual Refinement Network for Single-Shot Object Detection

Object detection methods fall into two categories, i.e., two-stage and s...
09/18/2017

StairNet: Top-Down Semantic Aggregation for Accurate One Shot Detection

One-stage object detectors such as SSD or YOLO already have shown promis...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.