# FSSD: Feature Fusion Single Shot Multibox Detector

Source: [FSSD: Feature Fusion Single Shot Multibox Detector](<https://www.sota2.com/research/paper/68fa72431e209131cea555cd>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:57:04.522Z

Authors: Zuoxin Li, Lu Yang, Fuqiang Zhou

Published: 2017-12-04T09:05:55.000Z

## Abstract

SSD (Single Shot Multibox Detector) is one of the best object detection algorithms with both high accuracy and fast speed. However, SSD's feature pyramid detection method makes it hard to fuse the features from different scales. In this paper, we proposed FSSD (Feature Fusion Single Shot Multibox Detector), an enhanced SSD with a novel and lightweight feature fusion module which can improve the performance significantly over SSD with just a little speed drop. In the feature fusion module, features from different layers with different scales are concatenated together, followed by some down-sampling blocks to generate new feature pyramid, which will be fed to multibox detectors to predict the final detection results. On the Pascal VOC 2007 test, our network can achieve 82.7 mAP (mean average precision) at the speed of 65.8 FPS (frame per second) with the input size 300$\\times$300 using a single Nvidia 1080Ti GPU. In addition, our result on COCO is also better than the conventional SSD with a large margin. Our FSSD outperforms a lot of state-of-the-art object detection algorithms in both aspects of accuracy and speed. Code is available at https://github.com/lzx1413/CAFFE\_SSD/tree/fssd.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Object Detection on PASCAL VOC 2012 (test)](<https://www.sota2.com/research/sota/object-detection-on-pascal-voc-2012-test.md>): Object Detection; PASCAL VOC 2012 (test); mAP: 82.7.

- [Object Detection on CARPK (test)](<https://www.sota2.com/research/sota/object-detection-on-carpk-test.md>): Object Detection; CARPK (test); AP50 (bbox): 87.59.

- [Object Detection on VOC 2007 (test)](<https://www.sota2.com/research/sota/object-detection-on-voc-2007-test.md>): Object Detection; VOC 2007 (test); AP@50: not recorded.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1712.00960>)

[PDF](<https://arxiv.org/pdf/1712.00960.pdf>)