wangzhe0623 / Obj_Det_Progress_Tracker

Object Detection Progress Tracker

Object Detection Progress Tracker

Last few years have seen great progress made in the domain of Object Detection. With powerful classification networks as backbone, more and more well-designed detection heads have been proposed to handle the dilemma of recognition and localization. This repo serves as a tracker of these progress.

2-stage

Model	Backbone	Tricks	VOC	COCO	FPS	Paper	Date	Note	Code
R-CNN	VGG16	-	58.5	-	-	Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation	-	CVPR2014 Oral	MATLAB
Fast R-CNN	VGG16	-	70.0	19.7	-	Fast R-CNN	15.04	CVPR2014 Oral	caffe
Faster R-CNN	VGG16	-	73.2	-	-	Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks	15.06	NIPS2015	MATLAB
Faster R-CNN+++	ResNet-101-C4	1,2,3	73.8	34.9	-	Deep Residual Learning for Image Recognition	15.12	CVPR2016 Best Paper
R-FCN	ResNet-101	4	80.5	29.9	6	R-FCN: Object Detection via Region-based Fully Convoluational Networks	16.05	NIPS2016	caffe
Deformable Conv	Aligned-Inception-ResNet	1,3	-	37.5	-	Deformable Convolutional Networks	17.03	ICCV2017 Oral	MXNet
Faster R-CNN w FPN	ResNet-101-FPN	-	-	36.2	-	Feature Pyramid Networks for Object Detection	16.12	CVPR2017 Poster	caffe2
Faster R-CNN by G-RMI	Inception-ResNet-v2	-	-	34.7	-	Speed/accuracy Trade-offs for Modern Convolutional object detectors	-	COCO206 winner	TesnsorFlow
Mask R-CNN	ResNeXt	6	-	39.8	-	Mask R-CNN	17.03	ICCV2017 Best Paper	caffe2
Light-haed R-CNN	ResNet-101-FPN	4,6	-	41.5	-	Light-Head R-CNN: In Defense of Two-stage Object Detector	17.11	-
Light-haed R-CNN	Xception	-	-	30.7	102	Light-Head R-CNN: In Defense of Two-stage Object Detector	17.11	-

1-stage

Model	Backbone	Tricks	VOC	COCO	FPS	Paper	Date	Note	Code
YOLO	Custom	-	63.4	-	45	YOLO: You Only Look Once	-	CVPR2016 Oral	darknet
SSD500	VGG16	-	75.1	24.4	23	SSD: Single Shot Detector	15.12	ECCV2016 Oral	caffe
SSD	ResNet-101	-	-	31.2	8	DSSD: Deconvolutional Single Shot Detector	17.01	-
YOLO v2	DarkNet-19	-	78.6	21.6	40	YOLO9000: Better, Faster, Stronger	-	CVPR2017	darknet
DSSD	ResNet-101	-	-	33.2	6	DSSD: Deconvolutional Single Shot Detector	17.01	-
RON384++	VGG16	3,7,8	77.6	27.4	-	RON: Reverse Connection with Objectness Prior Networks for Object Detection	-	CVPR2017	caffe
RetinaNet	ResNet-101-FPN	-	-	39.1	-	Focal Loss for Dense Object Detection	17.08	ICCV2017 Best student paper	caffe2
RefineDet512	VGG16	-	81.8	33.0	24.1	Single-Shot Refinement Neural Network for Object Detection	17.11	-	caffe
RefineDet512+	ResNet-101	3	-	41.8	-	Single-Shot Refinement Neural Network for Object Detection	17.11	-	caffe

Tricks list

1. box refinement
2. context
3. multi-scale testing
4. multi-scale training
5. OHEM
6. RoIAlign
7. box voting
8. flip

To be added

• FSSD
• DSOD
• GRP-DSOD
• [ ]

Disclaimer:

1. Pascal VOC AP results are evaluated with IOU 0.5. Models are trained on VOC07+12, tested on VOC07.
2. MS COCO results are reported with training on trainval35k, testing on test-dev set.
3. All code repos are official implementation.
4. Reported FPS are usually on GPU, not comparable actually.

My Notes(in Chinese) can be found here.