本文总结了近几年来的目标检测算法paper的pdf文档和在github上的代码地址
2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection intro: CVPR 2017 arxiv:https://arxiv.org/abs/1704.03414 paperhttp://abhinavsh.info/papers/pdfs/adversarialobjectdetectionpdf github(Catte):https://github.com/xiaolonwadversarial-frcnn Faster R-CNN Faster R-CNN: Towards Real-Time object Detection with Region Proposal Networks intro NIPs 2015 arxiv:http:/arxv.org/abs/1506.01497 gitxiv:http://www.gitxiv.com/posts/8pfpcvefdyn2gsgx/faster-r-cnn-towards-real-tiMe-objEct-detection-wIth-regiOn slideshttp://web.cs.hacettepe.edutr/-aykut/classes/spring2016/bil722/slides/w05-fasterr-cnn.pdf github(official,Matlab):https://github.corm/ShaogingRen/Fastercnn github(Caffe):https:/github.com/rbgirshick/py-faster-rcnn github(mxnet):https:/github.com/msracver/deformable-convnets/tree/master/Fasterrann github(pyTorch-recommend):https:/github.com//wyang/faster-rcnn.pytorch github:https:/github.com/mitmul/chainer-faster-rcnn github(Torch):https://github.com/andreaskaepfasler-rcnnLor github(torch)::https:github.com/ruotianluo/faster-rcnn-densecap-torch github(tensorflow):https://github.com/smallcorgi/faster-rcnntf github(tensorflow):https://github.com/charlesShang/tffrcnn github(c++demo):https:/igithub.com/yihanglou/fAsterrcnn-encapsulatIon-cplusplus github(Keras):https:/github.com/heron/keras-frcrin github:https://github.corm/eniac-xie/Faster-rcnin-resnet github(c++):https:/github.com/d-x-y/caffE-fasteR-rcnn/tree/dev R-CNN minus R intro: BMVC 2015 arxiv:http:/arxiv.org/abs/1506.06981 Faster R-CNN in MXNet with distributed implementation and data parallelization github:https:/igithub.com/dmlc/mxnet/tree/master/example/rcnn Contextual Priming and Feedback for Faster R-CNN intro: ECCV2016. Carnegie Mellon University paperhttpW/abhinavsh.infoicontextprimingfeedback.pdf posterhttp://ww.eccv2016.org/files/posters/p-1a-20.pdr An Implementation of Faster Rcnn with Study for Region Sampling intro: Technical Report, 3 pages. CMU arxiv:https://arxiv.orglabs/1702.02138 github:https:/github.com/endernewton/tf-faster-rcnn Interpretable R-CNN intro: North Carolina State University Alibaba keywords: AND-OR Graph(AOG) arxiv:https:/arxiv.orglabs/1711.05226 Light-Head R-CNN 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 3/20 2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 arxiv:https://arxiv.orglabs/1711.07264 github(offical):https:/github._com/zengarden/lighthead_rcnn github:https:/github.com/terrychenism/deformable-convnets/blob/master/rfcn/Symbols/resnetv1101rfcnlightpy#l784 Cascade R-cnn Cascade R-CNN: Delving into High Quality Object Detection arxiv:https://arxiv.orglabs/1712.00726 github:https:/github.com/zhaoweicaicascade-rcnn SPP-Net Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition intro: ECCV 2014/TPAMI 2015 arxiv:http:/larxiv.orgiabs/1406.4729 github:https:/github.com/shaoqingRen/sppnet noles: htlp: //zhangliang COIm/2014 09/13/ paper-note-sppneL DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection intro: PAMi 2016 intro: an extension of R-CNN box pre-training, cascade on region proposals, deformation layers and context representations projectpagehttp://www.ee.cuhk.edu.hk/%cb%9Cwouyang/projects/imagenetdeepld/index.html v: htlp: arxiv org/abs/1412.566 Object Detectors Emerge in Deep Scene CNNS ● Intro:|CLR2015 arxiv:http:/arxiv.org/abs/1412.6856 paperhttps://www.robots.ox.ac.uk/-vgg/rg/papers/zhouiclr15.pdf paperhttps://people.csail.mitedu/khosla/papers/iclr2015zhou.pdf slideshttp:/places.csail.mit.edu/slideicir2015.paf segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for object Detection intro CVPR 2015 ject(code+data):https://w.cs.torontoedu/-yukun/segdeepm.html arxiv:https://arxiv.org/abs/1502.04275 github:https://github.com/yknzhu/segDeepm Object Detection Networks on Convolutional Feature Maps · intro:TPAM2015 · keywords:NC aniv:http:/arxv.org/abs/1504.06066 Improving object Detection with Deep Convolutional Networks via Bayesian Optimization and structured Prediction arxiv:http:/arxv.org/abs/1504.03293 slideshttp://ww.ytzhang.net/files/publications/2015-cvpr-det-slides.pdf github:https:/github.com/yutingzhang/fgs-ob DeepBox: Learning Objectness with Convolutional Networks keywords: Deep Box arxiv:http:/arxiv.org/abs/1505.0214 github:https:/github.com/weichengkuo/deepBox 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 4/20 2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 You Only Look Once: Unified, Real-Time Object Detection Darknet arxiv:httparxv.org/abs/1506.02640 codehttps://pjreddie.com/darknet/yolov1 github:https:/igithaib.com/pjreddie/darknet olog:https://pjreddie.com/darknet/yolov1/ slideshttps://docs.googlecom/presentation/d/1aervtkg21khdd5lg6hgyhx5rpqzosgjg5rj1hP7bba/pUb?start=fAlse&loOp=fAlse&delAyms=3000&slide=id.p reddithttps://ww.reddit.com/r/machinclearniNg/comments/3a3m0o/realtiMeobjectdetectionwithyolo github:https:/igithub.com/gliese581gg/yolotensorflow github:https:/github.com/xingwangsfu/caffe-yolo github:https:/github.corr/frankzhangrui/darknel-yolo github:https://github.com/briskyhekun/py-darknet-yoLo github:https:/github.com/tommy-qichang/yolo.torch github:https:/github.com/frischzenger/yolo-wndows github:https:/github.com/alexeyab/yOlo-windows github:https:/github.cort/nilboY/tenisorflow-yolo darkflow-translate darknet to tensorflow. Load trained weights, retrain/fine-tune them using tensorflow, export constant graph def to C++ bloghttps://thtrieu.github.io/notes/yolo-tensorflow-graph-buffer-cpp github:https://github.com/thtrieu/darkflow Start Training YOLO with Our Own Data YOLO intro: train with customized data and class numbers/labels. Linux/Windows version for darknet blog:http://guanghaninfo/blog/en/my-worksitrain-yolo github:https:/github.com/guanghan/darKnet YOLO: Core ML versus MPSNNGraph intro: Tiny YOLO for iOS implemented using CoreML but also using the new MPS graph APl ologhttp://machinethink.net/blog/yolo-coreml-versus-mps-graph/ github:https://github.com/hollance/yolo-coreml-mpsnngraph TensorFlow YoLo object detection on Android 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 5/20 2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 Computer Vision in ioS-Object Detection blog:https:/sriraghu.com/2017/07/12/computer-vision-inl-ios-objecl-detection github:https:/github.com/r4ghu/ios-coreml-yolo YOLOV2 YOLO9000: Better, Faster, Stronger anxiv:https:/arxiv.orglabs/1612.08242 codehttp://pjreddie.comyolo9000/https:/pjreddie.com/darknet/yolov2 github(Chainer):https:/github.com/leetenki/yolov2 github(keras):https://github.com/allanzelener/yad2k github(pyTorch):httpsi/github.com/longcw/yolo2-pytorch github(tensorflow):https://github.com'hizhangp/yolotensorflow github(windows):https:/github.comalexeyab/daRknel github:https://github.com/choasup/caffe-yolog000 github:https:/github.com/philipperemy/yolo-9000 github(tensorflow):https:/github.com/kod-chen/yOlov2-tenSorflow github(keras):https:/github.com/yhcc/yolo2 github(Keras):https:/github.com/experiencer/keras-yolo2 github(tensorflow):https:/github.com/wojciechmorMulyolo2 darknet scripts intro: Auxilary scripts to work with (YoLo)darknet deep learning famework AKA-> How to generate YOLO anchors? github:https:/github.com/jumabek/darknetscripts Yolo_ mark: GUI for marking bounded boxes of objects in images for training Yolo v2 github:https:/github.com/alexeyab/yOlomark LightNet: Bringing pjreddie's DarkNet out of the shadows https:/github.coml/explosion/lightnet YOLO V2 Bounding Box Tool intro: Bounding box labeler tool to generate the training data in the format YoLo V2 requires github:https:/github.com/cartucho/yOlo-boundingbox-labeler-gui Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors intro: LRM is the first hard example mining strategy which could fit YoLOv2 perfectly and make it better applied in series of real scenarios where both real- time rate detection are strongly demanded arxiv:https://arxiv.orglabs/1804.04606 Object detection at 200 Frames Per Second intro: faster than Tiny-Yolo-V2 arxiv:https:/arxiv.orglabs/1805.06361 Event-based Convolutional Networks for Object Detection in Neuromorphic Cameras intro: YOLE-Object Detection in Neuromorphic Cameras anxiv:httpsi/arxiv.orglabs/1805.07931 OmniDetector: With Neural Networks to Bounding Boxes intro: a person detector on n fish-eye images of indoor scenes( NIPS 2018) arxiy:https:/arxiv.org/abs/1805.08503 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 6/20 2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 YOLOv 3 YOLOV3: An Incremental Improvement arxiv:httpsi/arxiv.org/abs/1804.02767 paperhttps://preddie.com/media/files/papers/yolov3.pdf codehttps://pjreddie.com/darknet/yolo/ github(official):https:/github.com/pjreddie/darknet github:httpsgithub.com/experiencor/keras-yolo3 github:https:/github.comiqqwweee/keras-yolo3 github:https://github.com/marvis/pytorch-yolo3 github:https:/github.com/ayooshkathuria/pytorch-yolo-v3 github:https:/github.comiayooshkathuria/yolov3tutorialfromscratch github:https:/github.cormieriklindernoren!pytorch-yolov3 YOLT You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery intro: Small Object Detection arxiv.https://arxivorglabs/1805.09512 github:https:/github.com/avanetten/yoit SSD SSD: Single Shot MultiBox Detector oc:△(cx,cy, conf:(c1, C2, (a)Image with Gt boxes b)8x8 feature map (c)4x 4 feature intro: ECCV 2016 Oral anxiv:http://anxiv.org/abs/1512.02325 paperhttp://w.cs.unc.edu/-miu/papers/Ssd.paf slideshttp://ww.cs.unc.edu/%7ewliu/papers/ssdeccv2016slidepdf github(official):https:/github.com/weiliu89/caffe/tree/ssd videohttp://weibo.com'p/2304447a2326da963254c963c97fb05dd3a973 github:https:/github.com/zhresholdimxmet-ssd github:https://github.com/zhresholdimxnet-ssd.cpp github:https:/github.com/rykov8/ssdkeras aith th. httncaithuib com/halancan/ssn Tencorflowr 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 7/20 2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 github( Caffe): htps: //github. com/ chuanqi305/MobileNet-SSD What's the diffience in performance between this new code you pushed and the previous code? #327 Https://github.com/weiliu89/caffe/issues/327 DSSD DSSD: Deconvolutional Single Shot Detector intro: UNC Chapel Hill Amazon hc arxiv:https://arxiv.org/abs/1701.06659 github:https://github.com/chengyangfu/caffe/tree/dssd ithub:https:/github.com/mtcloudvisIon/mnEt-dSsd mo:http://120.52.72.53/ww.cs.unc.edu/c3pr9ontcotd/-cyfu/dssdlalaland.mp4 Enhancement of SSD by concatenating feature maps for object detection intro: rainbow SSB (R-SSD) arxiv:https:/arxiv.orglabs/1705.09587 Context-aware Single-Shot Detector keywords: CSSD, DiCSSD, DeCSSD, effective receptive fields(ERFs), theoretical receptive fields(tRFs) anxiv:https:/arxiv.orglabs/1707.08682 Feature-Fused SSD: Fast Detection for Small Objects https://arxivorg/abs/1709.05054 FSSD FSSD: Feature Fusion single shot Multibox Detector https://arxiv.org/abs/1712.00960 Weaving Multi-scale Context for Single shot Detector intro: Weave Net keywords: fuse multi-scale information arxiv:https:/arxiv.orglabs/1712.03149 ESSD Extend the shallow part of single shot MultiBox Detector via Convolutional Neural Network httpsarxiv.org/abs/1801.05918 Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object Detection https://arxiv.org/abs/1802.06488 MDSSD MDSSD: Multi-scale Deconvolutional Single Shot Detector for small objects arxiv:https:/larxiv.orglabs/1805.07009 Pelee Pelee: A Real-Time Object Detection System on Mobile Devices https://github.com/robert-junWang/pelee intro: (ICLR 2018 workshop track) 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 8/20 2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 github:https:/lgithub.com/robert-junwAng/pelee Fire ssD Fire SSD: Wide Fire Modules based single Shot Detector on Edge Device intro: low cost, fast speed and high mAP on factor edge computing devices arxivchttpsarxiv.org/abs/1806.05363 R-FCN R-FCN: Object Detection via Region-based Fully Convolutional Networks anxiv:http:/arxiv.orgiabs/1605.06409 github:https://github.com/daijifengoo1/r-fcn github(mxnet):https:/github.com/msracver/deformable-convnets/tree/masteriRfcn github:https://github.com/orpine/py-r-fcn github:https:/github.com/pureDiors/pytorchRfCn github:https:/github.com/bharatsingh430/py-r-fcn-multigpu github:https:/github.corm/xdever/rfcn-lensorflov R-FCN-3000 at 30fps: Decoupling Detection and classification ttps: //arxiv.org/abs/1712.01802 Recycle deep features for better object detection arxiv:http:/ariv.org/abs/1607.05066 FPN Feature Pyramid Networks for Object Detection intro Facebook al Research arxiv:https:/arxiv.orglabs/1612.03144 Action-Driven Object Detection with Top-Down Visual Attentions arxiv:https://arxv.orglabs/1612.06704 Beyond Skip Connections: Top-Down Modulation for Object Detection intro: CMU UC berkeley google Research arxiv:https://arxiv.org/abs/1612.08851 Wide-Residual-Inception Networks for Real-time Object Detection intro: Inha University arxiv:https:/larxiv.orglabs/1702.01243 Attentional Network for Visual Object Detection intro: University of Maryland Mitsubishi Electric Research Laboratories arxiv:https:/arxiv.org/abs/1702.01478 Learning Chained Deep Features and classifiers for Cascade in Object Detection keywords: CC-Nct intro: chained cascade network(CC-Net)81.1% mAP on PASCAL VOC 2007 arxiv:https://arxiv.org/abs/1702.07054 DeNet: Scalable Real-time object Detection with Directed Sparse sampling 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 9/20 2018/8/27 目标检测( Object Detection)算法合集(持续更新ing)-CSD博客 arxiv:https:/arxv.orglabs/1703.10295 Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries intro: CVPR 2017 ariv:https://arxiv.org/abs/1704.03944 Spatial Memory for Context Reasoning in Object Detection arxiy:httpsarxiv.orglabs/1704.04224 Accurate Single Stage Detector Using Recurrent Rolling Convolution intro: CVPR 2017. Sense Time keywords: Recurrent Rolling Convolution(RRC) arxiv:https:/arxiv.orglabs/1704.05776 github:https:/github.com/xiachaoChen/rrcdetection Deep Occlusion Reasoning for Multi-Camera Multi-Target Detection httpsarxiv.org/abs/1704.05775 LCDet: LoW-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded systems intro: Embedded Vision Workshop in CVPR. UC San Diego Qualcomm Inc arxiv:https://arxiv.orglabs/1705.05922 Point Linking Network for Object Detection intro: Point Linking Network(PLN arxiv:https://arxiv.orglabs/1706.03646 Perceptual Generative Adversarial Networks for Small object Detection ttps: /arxiv org/abs/1706.05274 Few-shot object Detection https://arxiv.org/abs/1706.08249 Yes-Net: An effective Detector Based on global Information https://arxivorg/abs/1706.09180 SMC Faster R-CNN: Toward a scene-specialized multi-object detector https://arxiv.org/abs/1706.10217 Towards lightweight convolutional neural networks for object detection https:/arxivorg/abs/1707.01395 tON: Reverse Connection with Objectness Prior Networks for object Detection intro: CVPR 2017 arxiv:https:/larxiv.orglabs/1707.01691 github:https:/github.com/taokong/ron Mimicking Very Efficient Network for Object Detection intro: CVPR 2017. Sense Time Beihang University paperhttp://openaccess.thecvf.com/contentcvpr2017/papers/liMimickingveryEfficientCvpr2017paper.pdf Residual Features and Unified Prediction Network for Single Stage Detection 登录 注 https://blog.csdn.ret/amusi1994/article/details/8104292#yolo3 10/20