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https://github.com/daicoolb/Awesome-Object-Detections

object detection records
https://github.com/daicoolb/Awesome-Object-Detections

List: Awesome-Object-Detections

computer-vision deep-learning object-detection

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object detection records

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# Awesome-Object-Detection

object detection records



## API

  - [Tensorflow](https://github.com/tensorflow/models/tree/master/research/object_detection) Tensorflow API for object detection

  - [Soft-NMS](https://github.com/bharatsingh430/soft-nms) Soft-Nms that used to post-process object detection 

  

## Image Augmentation

  - [imgaug](https://github.com/aleju/imgaug) This python library helps you with augmenting images for your machine learning projects

  - [Augmentor](https://github.com/mdbloice/Augmentor) Augmentor is an image augmentation library in Python for machine learning.

  - [Image Augmentor](https://github.com/codebox/image_augmentor) A simple data augmentation tool for image files, intended for use with machine learning data sets.

  - [Image Augmentation](https://github.com/vxy10/ImageAugmentation) Generating additional data for unbalanced classes by jittering the original image.

  - [Data Augmentation](http://tflearn.org/data_augmentation/) Base class for applying common real-time data augmentation 



## Image Deduplication

  - [Hash C++](https://github.com/daicoolb/Awesome-Object-Detections/blob/master/sim_hash.cpp) Perception hash

  - [Image-deduplication-tool Python](https://github.com/mk-fg/image-deduplication-tool) simple tool to detect (and get rid of) similar images using perceptual hashing

  - [Imgdup](https://github.com/rif/imgdup) Visual similarity image finder and cleaner (image deduplication tool).

  

## BackBone

  - [FPN](http://cn.arxiv.org/pdf/1612.03144.pdf) Feature Pyramid Networks for Object Detection

  - [DetNet](http://cn.arxiv.org/pdf/1804.06215.pdf) DetNet: A Backbone network for Object Detection

  - [MegDet](http://cn.arxiv.org/pdf/1711.07240.pdf) MegDet: A Large Mini-Batch Object Detector



## One stage 

  - [Yolov1](http://cn.arxiv.org/pdf/1506.02640.pdf) You Only Look Once: Unified, Real-Time Object Detection [darknet](https://github.com/pjreddie/darknet) [caffe](https://github.com/xingwangsfu/caffe-yolo)

  - [Yolov2](http://cn.arxiv.org/pdf/1612.08242.pdf) YOLO9000:Better, Faster, Stronger [tensorflow](https://github.com/WojciechMormul/yolo2) [pytorch](https://github.com/longcw/yolo2-pytorch) [caffe](https://github.com/gklz1982/caffe-yolov2)

  - [Yolov3](http://cn.arxiv.org/pdf/1804.02767.pdf) YOLOv3: An Incremental Improvement [pytorch](https://github.com/ayooshkathuria/pytorch-yolo-v3) [keras](https://github.com/qqwweee/keras-yolo3)

  - [Yolov4](https://arxiv.org/pdf/2004.10934.pdf) YOLOv4: Optimal Speed and Accuracy of Object Detection [pytorch](https://github.com/Tianxiaomo/pytorch-YOLOv4) [tensorflow](https://github.com/hunglc007/tensorflow-yolov4-tflite)

  - [Yolov5]() [pytorch](https://github.com/ultralytics/yolov5)

  - [SSD](http://cn.arxiv.org/pdf/1512.02325.pdf) SSD: Single Shot MultiBox Detector [caffe](https://github.com/weiliu89/caffe/tree/ssd) [tensorflow](https://github.com/balancap/SSD-Tensorflow)

  - [DSSD](http://cn.arxiv.org/pdf/1701.06659.pdf) DSSD : Deconvolutional Single Shot Detector [caffe](https://github.com/chengyangfu/caffe/tree/dssd)

  - [RFB-SSD](http://cn.arxiv.org/pdf/1711.07767.pdf) Receptive Field Block Net for Accurate and Fast Object Detection [pytorch](https://github.com/ruinmessi/RFBNet)

  - [DES](http://cn.arxiv.org/pdf/1712.00433.pdf) Single-Shot Object Detection with Enriched Semantics 

  - [STDN](http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/1376.pdf) Scale-Transferrable Object Detection [pytorch](https://github.com/arvention/STDN)

  - [RetinaNet](http://cn.arxiv.org/pdf/1708.02002.pdf) Focal Loss for Dense Object Detection [caffe](https://github.com/chuanqi305/FocalLoss) [tensorflow](https://github.com/CasiaFan/tensorflow_retinanet)

  - [RefineDet](http://cn.arxiv.org/pdf/1711.06897.pdf) Single-Shot Refinement Neural Network for Object Detection [caffe](https://github.com/sfzhang15/RefineDet)

  - [CornerNet](http://cn.arxiv.org/pdf/1808.01244.pdf) CornerNet: Detecting Objects as Paired Keypoints [tensorflow](https://github.com/makalo/CornerNet)

  - [FCOS](http://cn.arxiv.org/pdf/1904.01355.pdf) Fully Convolutional One-Stage Object Detection [pytorch](https://github.com/tianzhi0549/FCOS)

  - [ExtremeNet](http://cn.arxiv.org/pdf/1901.08043.pdf) Bottom-up Object Detection by Grouping Extreme and Center Points [pytorch](https://github.com/xingyizhou/ExtremeNet)

  - [M2det](https://qijiezhao.github.io/imgs/m2det.pdf) M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network [pytorch](https://github.com/qijiezhao/M2Det)

  - [CornerNet-Lite](https://arxiv.org/pdf/1904.08900.pdf) CornerNet-Lite: Efficient Keypoint Based Object Detection [pytorch](https://github.com/princeton-vl/CornerNet-Lite)

  - [Scratchdet](https://arxiv.org/abs/1810.08425) ScratchDet: Training Single-Shot Object Detectors From Scratch [pytorch](https://github.com/KimSoybean/ScratchDet)

  

## Two stage

  - [RCNN](http://cn.arxiv.org/pdf/1311.2524.pdf) Rich feature hierarchies for accurate object detection and semantic segmentation [caffe](https://github.com/rbgirshick/rcnn)

  - [Fast RCNN](http://cn.arxiv.org/pdf/1504.08083.pdf) Fast RCNN [caffe](https://github.com/rbgirshick/fast-rcnn)

  - [Faster RCNN](http://cn.arxiv.org/pdf/1506.01497.pdf) Towards Real-Time Object Detection with Region Proposal Networks [caffe](https://github.com/rbgirshick/py-faster-rcnn) [tensorflow](https://github.com/smallcorgi/Faster-RCNN_TF) [pytorch](https://github.com/jwyang/faster-rcnn.pytorch)

  - [Mask RCNN](http://cn.arxiv.org/pdf/1703.06870.pdf) Mask RCNN [keras](https://github.com/matterport/Mask_RCNN) [caffe2](https://github.com/facebookresearch/Detectron) [tensorflow](https://github.com/CharlesShang/FastMaskRCNN) [pytorch](https://github.com/multimodallearning/pytorch-mask-rcnn)

  - [R-FCN](http://cn.arxiv.org/pdf/1605.06409.pdf) R-FCN: Object Detection via Region-based Fully Convolutional Networks [caffe](https://github.com/YuwenXiong/py-R-FCN) [tensorflow](https://github.com/xdever/RFCN-tensorflow) [pytorch](https://github.com/PureDiors/pytorch_RFCN)

  - [Light Head RCNN](http://cn.arxiv.org/pdf/1711.07264.pdf) Light-Head R-CNN: In Defense of Two-Stage Object Detector [tensorflow](https://github.com/zengarden/light_head_rcnn) [pytorch](https://github.com/Sundrops/pytorch-faster-rcnn)

  - [Cascade RCNN](http://cn.arxiv.org/pdf/1712.00726.pdf) Cascade R-CNN: Delving into High Quality Object Detection [caffe](https://github.com/zhaoweicai/cascade-rcnn)

  - [PANet](http://cn.arxiv.org/pdf/1803.01534.pdf) Path Aggregation Network for Instance Segmentation [pytorch](https://github.com/ShuLiu1993/PANet)

  - [Mask Scoring R-CNN](http://cn.arxiv.org/pdf/1903.00241.pdf) Mask Scoring R-CNN [pytorch](https://github.com/zjhuang22/maskscoring_rcnn)

  - [TridentNet](https://arxiv.org/abs/1901.01892) TridentNet：Scale-Aware Trident Networks for Object Detection [mxnet](https://github.com/TuSimple/simpledet)

  - [Cascade R-CNN](https://arxiv.org/abs/1906.09756) Cascade R-CNN：High Quality Object Detection and Instance Segmentation [pytorch](https://github.com/zhaoweicai/Detectron-Cascade-RCNN)

  - [KL-LOSS](https://arxiv.org/abs/1809.08545) Bounding Box Regression with Uncertainty for Accurate Object Detection [caffe2](https://github.com/yihui-he/KL-Loss)

  - [Libra-RCNN](https://arxiv.org/pdf/1904.02701.pdf) Libra R-CNN: Towards Balanced Learning for Object Detection [pytorch](https://github.com/OceanPang/Libra_R-CNN)

  - [Grid-RCNN](https://arxiv.org/abs/1811.12030) Grid R-CNN [pytorch](https://github.com/STVIR/Grid-R-CNN)

  - [CBNet](https://aaai.org/Papers/AAAI/2020GB/AAAI-LiuY.1833.pdf) CBNet: A Novel Composite Backbone Network Architecture for Object Detection [pytorch](https://github.com/VDIGPKU/CBNet)

  - [TSD](https://arxiv.org/pdf/2003.07557.pdf) 1st Place Solutions for OpenImage2019 - Object Detection and Instance Segmentation [pytorch](https://github.com/Sense-X/TSD)

  - [DetectoRS](https://arxiv.org/pdf/2006.02334.pdf) DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution [pytorch](https://github.com/joe-siyuan-qiao/DetectoRS)

  - [EfficientDet](https://arxiv.org/pdf/1911.09070.pdf) EfficientDet: Scalable and Efficient Object Detection [tensorflow](https://github.com/google/automl/tree/master/efficientdet) [pytorch](https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch)

  - [D2Det](https://openaccess.thecvf.com/content_CVPR_2020/papers/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.pdf) D2Det: Towards High Quality Object Detection and Instance Segmentation [pytorch](https://github.com/JialeCao001/D2Det)

   

## Recent Papers

  - [PrROI](https://arxiv.org/pdf/1807.11590.pdf) Acquisition of Localization confidence for accurate object detection ECCV2018

  - [FreeAnchor](https://arxiv.org/pdf/1909.02466.pdf) FreeAnchor: Learning to Match Anchors for Visual 

Object Detection [pytorch](https://github.com/zhangxiaosong18/FreeAnchor) NIPS2019

  - [CBNet](https://arxiv.org/pdf/1909.03625.pdf) CBNet: A Novel Composite Backbone Network Architecture for Object Detection

[caffe2](https://github.com/PKUbahuangliuhe/CBNet) 

  - [CenterNet](https://arxiv.org/pdf/1904.08189.pdf) CenterNet: Keypoint Triplets for Object Detection [pytorch](https://github.com/Duankaiwen/CenterNet)