deep learning object detection

A paper list of object detection using deep learning. I worte this page with reference to this survey paper and searching and searching..

Last updated: 2019/01/02

Update log

2018/9/18 - update all of recent papers and make some diagram about history of object detection using deep learning. 2018/9/26 - update codes of papers. (official and unofficial)
2018/october - update 5 papers and performance table.
2018/november - update 9 papers.
2018/december - update 8 papers and and performance table and add new diagram(2019 version!!).

paper list from 2014 to now(2019)

performance table

Detector	VOC07 (mAP@IoU=0.5)	VOC12 (mAP@IoU=0.5)	COCO (mAP)	Published In
R-CNN	58.5	-	-	CVPR'14
SPP-Net	59.2	-	-	ECCV'14
MR-CNN	78.2 (07+12)	73.9 (07+12)	-	ICCV'15
Fast R-CNN	70.0 (07+12)	68.4 (07++12)	-	ICCV'15
Faster R-CNN	73.2 (07+12)	70.4 (07++12)	-	NIPS'15
YOLO v1	66.4 (07+12)	57.9 (07++12)	-	CVPR'16
G-CNN	66.8	66.4 (07+12)	-	CVPR'16
AZNet	70.4	-	22.3	CVPR'16
ION	80.1	77.9	33.1	CVPR'16
HyperNet	76.3 (07+12)	71.4 (07++12)	-	CVPR'16
OHEM	78.9 (07+12)	76.3 (07++12)	22.4	CVPR'16
MPN	-	-	33.2	BMVC'16
SSD	76.8 (07+12)	74.9 (07++12)	-	ECCV'16
GBDNet	77.2 (07+12)	-	27.0	ECCV'16
CPF	76.4 (07+12)	72.6 (07++12)	-	ECCV'16
R-FCN	79.5 (07+12)	77.6 (07++12)	29.9	NIPS'16
DeepID-Net	69.0	-	-	PAMI'16
NoC	71.6 (07+12)	68.8 (07+12)	27.2	TPAMI'16
DSSD	81.5 (07+12)	80.0 (07++12)	-	arXiv'17
TDM	-	-	37.3	CVPR'17
FPN	-	-	36.2	CVPR'17
YOLO v2	78.6 (07+12)	73.4 (07++12)	-	CVPR'17
RON	77.6 (07+12)	75.4 (07++12)	-	CVPR'17
DeNet	77.1 (07+12)	73.9 (07++12)	33.8	ICCV'17
CoupleNet	82.7 (07+12)	80.4 (07++12)	34.4	ICCV'17
RetinaNet	-	-	39.1	ICCV'17
DSOD	77.7 (07+12)	76.3 (07++12)	-	ICCV'17
SMN	70.0	-	-	ICCV'17
Light-Head R-CNN	-	-	41.5	arXiv'17
YOLO v3	-	-	33.0	arXiv'18
SIN	76.0 (07+12)	73.1 (07++12)	23.2	CVPR'18
STDN	80.9 (07+12)	-	-	CVPR'18
RefineDet	83.8 (07+12)	83.5 (07++12)	41.8	CVPR'18
SNIP	-	-	45.7	CVPR'18
Relation-Network	-	-	32.5	CVPR'18
Cascade R-CNN	-	-	42.8	CVPR'18
MLKP	80.6 (07+12)	77.2 (07++12)	28.6	CVPR'18
RFBNet	82.2 (07+12)	-	-	ECCV'18
CornerNet	-	-	42.1	ECCV'18
Pelee	76.4 (07+12)	-	-	NIPS'18
HKRM	78.8 (07+12)	-	37.8	NIPS'18
M2Det	-	-	44.2	AAAI'19

2014
2015
2016
2017
2018
2019

2014

[R-CNN] Rich feature hierarchies for accurate object detection and semantic segmentation | Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik | [CVPR' 14] |[pdf] [official code - caffe]
[OverFeat] OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks | Pierre Sermanet, et al. | [ICLR' 14] |[pdf] [official code - torch]
[MultiBox] Scalable Object Detection using Deep Neural Networks | Dumitru Erhan, et al. | [CVPR' 14] |[pdf]
[SPP-Net] Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition | Kaiming He, et al. | [ECCV' 14] |[pdf] [official code - caffe] [unofficial code - keras] [unofficial code - tensorflow]

2015

[MR-CNN] Object detection via a multi-region & semantic segmentation-aware CNN model | Spyros Gidaris, Nikos Komodakis | [ICCV' 15] |[pdf] [official code - caffe]
[DeepBox] DeepBox: Learning Objectness with Convolutional Networks | Weicheng Kuo, Bharath Hariharan, Jitendra Malik | [ICCV' 15] |[pdf] [official code - caffe]
[AttentionNet] AttentionNet: Aggregating Weak Directions for Accurate Object Detection | Donggeun Yoo, et al. | [ICCV' 15] |[pdf]
[Fast R-CNN] Fast R-CNN | Ross Girshick | [ICCV' 15] |[pdf] [official code - caffe]
[DeepProposal] DeepProposal: Hunting Objects by Cascading Deep Convolutional Layers | Amir Ghodrati, et al. | [ICCV' 15] |[pdf] [official code - matconvnet]
[Faster R-CNN, RPN] Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks | Shaoqing Ren, et al. | [NIPS' 15] |[pdf] [official code - caffe] [unofficial code - tensorflow] [unofficial code - pytorch]

2016

[YOLO v1] You Only Look Once: Unified, Real-Time Object Detection | Joseph Redmon, et al. | [CVPR' 16] |[pdf] [official code - c]
[G-CNN] G-CNN: an Iterative Grid Based Object Detector | Mahyar Najibi, et al. | [CVPR' 16] |[pdf]
[AZNet] Adaptive Object Detection Using Adjacency and Zoom Prediction | Yongxi Lu, Tara Javidi. | [CVPR' 16] |[pdf]
[ION] Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks | Sean Bell, et al. | [CVPR' 16] |[pdf]
[HyperNet] HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection | Tao Kong, et al. | [CVPR' 16] |[pdf]
[OHEM] Training Region-based Object Detectors with Online Hard Example Mining | Abhinav Shrivastava, et al. | [CVPR' 16] |[pdf] [official code - caffe]
[CRAPF] CRAFT Objects from Images | Bin Yang, et al. | [CVPR' 16] |[pdf] [official code - caffe]
[MPN] A MultiPath Network for Object Detection | Sergey Zagoruyko, et al. | [BMVC' 16] |[pdf] [official code - torch]
[SSD] SSD: Single Shot MultiBox Detector | Wei Liu, et al. | [ECCV' 16] |[pdf] [official code - caffe] [unofficial code - tensorflow] [unofficial code - pytorch]
[GBDNet] Crafting GBD-Net for Object Detection | Xingyu Zeng, et al. | [ECCV' 16] |[pdf] [official code - caffe]
[CPF] Contextual Priming and Feedback for Faster R-CNN | Abhinav Shrivastava and Abhinav Gupta | [ECCV' 16] |[pdf]
[MS-CNN] A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection | Zhaowei Cai, et al. | [ECCV' 16] |[pdf] [official code - caffe]
[R-FCN] R-FCN: Object Detection via Region-based Fully Convolutional Networks | Jifeng Dai, et al. | [NIPS' 16] |[pdf] [official code - caffe] [unofficial code - caffe]
[PVANET] PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection | Kye-Hyeon Kim, et al. | [NIPSW' 16] |[pdf] [official code - caffe]
[DeepID-Net] DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection | Wanli Ouyang, et al. | [PAMI' 16] |[pdf]
[NoC] Object Detection Networks on Convolutional Feature Maps | Shaoqing Ren, et al. | [TPAMI' 16] |[pdf]

2017

[DSSD] DSSD : Deconvolutional Single Shot Detector | Cheng-Yang Fu1, et al. | [arXiv' 17] |[pdf] [official code - caffe]
[TDM] Beyond Skip Connections: Top-Down Modulation for Object Detection | Abhinav Shrivastava, et al. | [CVPR' 17] |[pdf]
[FPN] Feature Pyramid Networks for Object Detection | Tsung-Yi Lin, et al. | [CVPR' 17] |[pdf] [unofficial code - caffe]
[YOLO v2] YOLO9000: Better, Faster, Stronger | Joseph Redmon, Ali Farhadi | [CVPR' 17] |[pdf] [official code - c] [unofficial code - caffe] [unofficial code - tensorflow] [unofficial code - tensorflow] [unofficial code - pytorch]
[RON] RON: Reverse Connection with Objectness Prior Networks for Object Detection | Tao Kong, et al. | [CVPR' 17] |[pdf] [official code - caffe] [unofficial code - tensorflow]
[RSA] Recurrent Scale Approximation for Object Detection in CNN | Yu Liu, et al. | | [ICCV' 17] |[pdf] [official code - caffe]
[DCN] Deformable Convolutional Networks | Jifeng Dai, et al. | [ICCV' 17] |[pdf] [official code - mxnet] [unofficial code - tensorflow] [unofficial code - pytorch]
[DeNet] DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling | Lachlan Tychsen-Smith, Lars Petersson | [ICCV' 17] |[pdf] [official code - theano]
[CoupleNet] CoupleNet: Coupling Global Structure with Local Parts for Object Detection | Yousong Zhu, et al. | [ICCV' 17] |[pdf] [official code - caffe]
[RetinaNet] Focal Loss for Dense Object Detection | Tsung-Yi Lin, et al. | [ICCV' 17] |[pdf] [official code - keras] [unofficial code - pytorch] [unofficial code - mxnet] [unofficial code - tensorflow]
[Mask R-CNN] Mask R-CNN | Kaiming He, et al. | [ICCV' 17] |[pdf] [official code - caffe2] [unofficial code - tensorflow] [unofficial code - tensorflow] [unofficial code - pytorch]
[DSOD] DSOD: Learning Deeply Supervised Object Detectors from Scratch | Zhiqiang Shen, et al. | [ICCV' 17] |[pdf] [official code - caffe] [unofficial code - pytorch]
[SMN] Spatial Memory for Context Reasoning in Object Detection | Xinlei Chen, Abhinav Gupta | [ICCV' 17] |[pdf]
[Light-Head R-CNN] Light-Head R-CNN: In Defense of Two-Stage Object Detector | Zeming Li, et al. | [arXiv' 17] |[pdf] [official code - tensorflow]

2018

[YOLO v3] YOLOv3: An Incremental Improvement | Joseph Redmon, Ali Farhadi | [arXiv' 18] |[pdf] [official code - c] [unofficial code - pytorch] [unofficial code - pytorch] [unofficial code - keras] [unofficial code - tensorflow]
[ZIP] Zoom Out-and-In Network with Recursive Training for Object Proposal | Hongyang Li, et al. | [IJCV' 18] |[pdf] [official code - caffe]
[SIN] Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships | Yong Liu, et al. | [CVPR' 18] |[pdf] [official code - tensorflow]
[STDN] Scale-Transferrable Object Detection | Peng Zhou, et al. | [CVPR' 18] |[pdf]
[RefineDet] Single-Shot Refinement Neural Network for Object Detection | Shifeng Zhang, et al. | [CVPR' 18] |[pdf] [official code - caffe] [unofficial code - chainer] [unofficial code - pytorch]
[MegDet] MegDet: A Large Mini-Batch Object Detector | Chao Peng, et al. | [CVPR' 18] |[pdf]
[DA Faster R-CNN] Domain Adaptive Faster R-CNN for Object Detection in the Wild | Yuhua Chen, et al. | [CVPR' 18] |[pdf] [official code - caffe]
[SNIP] An Analysis of Scale Invariance in Object Detection – SNIP | Bharat Singh, Larry S. Davis | [CVPR' 18] |[pdf]
[Relation-Network] Relation Networks for Object Detection | Han Hu, et al. | [CVPR' 18] |[pdf] [official code - mxnet]
[Cascade R-CNN] Cascade R-CNN: Delving into High Quality Object Detection | Zhaowei Cai, et al. | [CVPR' 18] |[pdf] [official code - caffe]
Finding Tiny Faces in the Wild with Generative Adversarial Network | Yancheng Bai, et al. | [CVPR' 18] |[pdf]
[MLKP] Multi-scale Location-aware Kernel Representation for Object Detection | Hao Wang, et al. | [CVPR' 18] |[pdf] [official code - caffe]
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation | Naoto Inoue, et al. | [CVPR' 18] |[pdf] [official code - chainer]
[STDnet] STDnet: A ConvNet for Small Target Detection | Brais Bosquet, et al. | [BMVC' 18] |[pdf]
[RFBNet] Receptive Field Block Net for Accurate and Fast Object Detection | Songtao Liu, et al. | [ECCV' 18] |[pdf] [official code - pytorch]
Zero-Annotation Object Detection with Web Knowledge Transfer | Qingyi Tao, et al. | [ECCV' 18] |[pdf]
[CornerNet] CornerNet: Detecting Objects as Paired Keypoints | Hei Law, et al. | [ECCV' 18] |[pdf] [official code - pytorch]
[ShapeShifter] ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector | Shang-Tse Chen, et al. | [ECML-PKDD' 18] |[pdf] [official code - tensorflow]
[Pelee] Pelee: A Real-Time Object Detection System on Mobile Devices | Jun Wang, et al. | [NIPS' 18] |[pdf] [official code - caffe]
[HKRM] Hybrid Knowledge Routed Modules for Large-scale Object Detection | ChenHan Jiang, et al. | [NIPS' 18] |[pdf]
[MetaAnchor] MetaAnchor: Learning to Detect Objects with Customized Anchors | Tong Yang, et al. | [NIPS' 18] |[pdf]
[SNIPER] SNIPER: Efficient Multi-Scale Training | Bharat Singh, et al. | [NIPS' 18] |[pdf]

2019

[M2Det] M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network | Qijie Zhao, et al. | [AAAI' 19] |[pdf]
[CAMOU] CAMOU: Learning Physical Vehicle Camouflages to Adversarially Attack Detectors in the Wild | Yang Zhang, et al. | [ICLR' 19] |[pdf]

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