序号 |
时间 |
论文名字 |
会议 |
git |
1 |
2015.12.8 |
SSD Deconvolutional Single Shot Detector |
ECCV2016 |
|
2 |
2017.1.23 |
DSSD Deconvolutional Single Shot Detector |
|
|
3 |
2017.5.26 |
R-SSD Enhancement of SSD by concatenating feature maps for object detection |
|
|
4 |
2017.07.18 |
RUN:Residual Features and Unified Prediction Network for Single Stage Detection |
|
git |
5 |
2017.7.26 |
Detecting Small Signs from Large Images |
|
|
6 |
2017.8.17 |
S3FD Single Shot Scale-invariant Face Detector |
|
|
7 |
2016.8.24 |
Online Real-time Multiple Spatiotemporal Action Localisation and Prediction |
ICCV 2017 |
git |
8 |
2017.8.27 |
Context-aware single-shot detector |
|
|
9 |
2017.9.15 |
Feature-Fused SSD: Fast Detection for Small Objects |
|
|
10 |
2017.11.18 |
Single-Shot Refinement Neural Network for Object Detection |
|
git |
11 |
2017.11.27 |
Receptive Field Block Net for Accurate and Fast Object Detection |
|
git |
12 |
2017.12.1 |
Single-Shot Object Detection with Enriched Semantics |
|
|
13 |
2017.12.4 |
FSSD: Feature Fusion Single Shot Multibox Detector |
|
|
14 |
2017.12.8 |
Weaving Multi-scale Context for Single Shot Detector |
|
|
训练条件:VOC07+12
对比条件: (T):Titanx Maxwell (P):Titan X Pascal GPU
Speed(P)=2*Speed(T)
以下数据全部来自论文统计
序号 |
方法 |
输入大小 |
基础网络 |
速度fps |
mAP(VOC07) |
mAP(VOC12) |
备注 |
1 |
SSD |
300 |
VGG16 |
46 |
77.2 |
75.8 |
|
2 |
DSSD |
300 |
Resnet-101 |
9.5 |
78.6 |
76.3 |
|
3 |
RefineDet |
320 |
VGG16 |
40.3 |
80 |
78.1 |
|
4 |
DES |
300 |
VGG16 |
34 |
79.5 |
77 |
67.8(P) |
5 |
DSOD |
300 |
DS/64-192-48-1 |
17.4 |
77.7 |
- |
|
6 |
R-SSD |
300 |
VGG16 |
37.1 |
78.5 |
- |
|
7 |
RUN3WAY |
300 |
VGG16 |
40 |
79.2 |
|
|
8 |
FSSD |
300 |
VGG16 |
33 |
78.8 |
- |
65.6(P) |
9 |
DiCSSD |
300 |
VGG16 |
40.8 |
78.1 |
- |
- |
10 |
DeCSSD |
300 |
VGG16 |
39.8 |
77.6 |
|
|
11 |
Proposed element-sum model |
300 |
VGG16 |
43 |
78.9 |
|
|
12 |
RFBNet |
300 |
VGG16 |
43 |
80.5 |
|
|
13 |
RFBNet |
300 |
VGG16 |
83 |
80.5 |
|
|
- |
- |
|
|
|
|
|
|
序号 |
方法 |
输入大小 |
基础网络 |
速度fps |
mAP(VOC07) |
mAP(VOC12) |
备注 |
1 |
SSD |
512 |
VGG16 |
19 |
79.8 |
78.5 |
|
2 |
DSSD |
513 |
Resnet-101 |
5.5 |
81.5 |
80 |
|
3 |
RefineDet |
512 |
VGG16 |
24.1 |
81.8 |
80.1 |
|
4 |
DES |
512 |
VGG16 |
14 |
81.6 |
80.2 |
27.2(P) |
5 |
R-SSD |
512 |
VGG16 |
15.8 |
80.8 |
|
|
6 |
RUN3WAY |
512 |
VGG16 |
19.5 |
80.9 |
|
|
7 |
FSSD |
512 |
VGG16 |
18 |
80.9 |
- |
35.7(P) |
8 |
RFB |
512 |
VGG16 |
18 |
82.2 |
|
|
9 |
RFBNet |
512 |
VGG16 |
38 |
82.23 |
|
|