{"id":7190,"url":"https://github.com/daicoolb/Awesome-Object-Detections","name":"Awesome-Object-Detections","description":"object detection records","projects_count":54,"last_synced_at":"2026-07-30T21:00:25.521Z","repository":{"id":43600981,"uuid":"139548887","full_name":"daicoolb/Awesome-Object-Detections","owner":"daicoolb","description":"object detection records","archived":false,"fork":false,"pushed_at":"2020-07-01T14:15:58.000Z","size":66,"stargazers_count":64,"open_issues_count":0,"forks_count":12,"subscribers_count":5,"default_branch":"master","last_synced_at":"2026-07-11T20:03:16.399Z","etag":null,"topics":["computer-vision","deep-learning","object-detection"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/daicoolb.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2018-07-03T08:00:24.000Z","updated_at":"2025-10-04T17:06:36.000Z","dependencies_parsed_at":"2022-08-26T03:41:58.957Z","dependency_job_id":null,"html_url":"https://github.com/daicoolb/Awesome-Object-Detections","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/daicoolb/Awesome-Object-Detections","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daicoolb%2FAwesome-Object-Detections","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daicoolb%2FAwesome-Object-Detections/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daicoolb%2FAwesome-Object-Detections/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daicoolb%2FAwesome-Object-Detections/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/daicoolb","download_url":"https://codeload.github.com/daicoolb/Awesome-Object-Detections/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daicoolb%2FAwesome-Object-Detections/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":36091646,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-07-20T02:08:10.276Z","status":"online","status_checked_at":"2026-07-30T02:00:05.956Z","response_time":106,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-12T13:37:13.852Z","updated_at":"2026-07-30T21:00:25.522Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Two stage","API","Image Augmentation","BackBone","One stage","Recent Papers","Image Deduplication"],"sub_categories":[],"readme":"# Awesome-Object-Detection\nobject detection records\n\n## API\n  - [Tensorflow](https://github.com/tensorflow/models/tree/master/research/object_detection) Tensorflow API for object detection\n  - [Soft-NMS](https://github.com/bharatsingh430/soft-nms) Soft-Nms that used to post-process object detection \n  \n## Image Augmentation\n  - [imgaug](https://github.com/aleju/imgaug) This python library helps you with augmenting images for your machine learning projects\n  - [Augmentor](https://github.com/mdbloice/Augmentor) Augmentor is an image augmentation library in Python for machine learning.\n  - [Image Augmentor](https://github.com/codebox/image_augmentor) A simple data augmentation tool for image files, intended for use with machine learning data sets.\n  - [Image Augmentation](https://github.com/vxy10/ImageAugmentation) Generating additional data for unbalanced classes by jittering the original image.\n  - [Data Augmentation](http://tflearn.org/data_augmentation/) Base class for applying common real-time data augmentation \n\n## Image Deduplication\n  - [Hash C++](https://github.com/daicoolb/Awesome-Object-Detections/blob/master/sim_hash.cpp) Perception hash\n  - [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\n  - [Imgdup](https://github.com/rif/imgdup) Visual similarity image finder and cleaner (image deduplication tool).\n  \n## BackBone\n  - [FPN](http://cn.arxiv.org/pdf/1612.03144.pdf) Feature Pyramid Networks for Object Detection\n  - [DetNet](http://cn.arxiv.org/pdf/1804.06215.pdf) DetNet: A Backbone network for Object Detection\n  - [MegDet](http://cn.arxiv.org/pdf/1711.07240.pdf) MegDet: A Large Mini-Batch Object Detector\n\n## One stage \n  - [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)\n  - [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)\n  - [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)\n  - [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)\n  - [Yolov5]() [pytorch](https://github.com/ultralytics/yolov5)\n  - [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)\n  - [DSSD](http://cn.arxiv.org/pdf/1701.06659.pdf) DSSD : Deconvolutional Single Shot Detector [caffe](https://github.com/chengyangfu/caffe/tree/dssd)\n  - [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)\n  - [DES](http://cn.arxiv.org/pdf/1712.00433.pdf) Single-Shot Object Detection with Enriched Semantics \n  - [STDN](http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/1376.pdf) Scale-Transferrable Object Detection [pytorch](https://github.com/arvention/STDN)\n  - [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)\n  - [RefineDet](http://cn.arxiv.org/pdf/1711.06897.pdf) Single-Shot Refinement Neural Network for Object Detection [caffe](https://github.com/sfzhang15/RefineDet)\n  - [CornerNet](http://cn.arxiv.org/pdf/1808.01244.pdf) CornerNet: Detecting Objects as Paired Keypoints [tensorflow](https://github.com/makalo/CornerNet)\n  - [FCOS](http://cn.arxiv.org/pdf/1904.01355.pdf) Fully Convolutional One-Stage Object Detection [pytorch](https://github.com/tianzhi0549/FCOS)\n  - [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)\n  - [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)\n  - [CornerNet-Lite](https://arxiv.org/pdf/1904.08900.pdf) CornerNet-Lite: Efficient Keypoint Based Object Detection [pytorch](https://github.com/princeton-vl/CornerNet-Lite)\n  - [Scratchdet](https://arxiv.org/abs/1810.08425) ScratchDet: Training Single-Shot Object Detectors From Scratch [pytorch](https://github.com/KimSoybean/ScratchDet)\n  \n## Two stage\n  - [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)\n  - [Fast RCNN](http://cn.arxiv.org/pdf/1504.08083.pdf) Fast RCNN [caffe](https://github.com/rbgirshick/fast-rcnn)\n  - [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)\n  - [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)\n  - [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)\n  - [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)\n  - [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)\n  - [PANet](http://cn.arxiv.org/pdf/1803.01534.pdf) Path Aggregation Network for Instance Segmentation [pytorch](https://github.com/ShuLiu1993/PANet)\n  - [Mask Scoring R-CNN](http://cn.arxiv.org/pdf/1903.00241.pdf) Mask Scoring R-CNN [pytorch](https://github.com/zjhuang22/maskscoring_rcnn)\n  - [TridentNet](https://arxiv.org/abs/1901.01892) TridentNet：Scale-Aware Trident Networks for Object Detection [mxnet](https://github.com/TuSimple/simpledet)\n  - [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)\n  - [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)\n  - [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)\n  - [Grid-RCNN](https://arxiv.org/abs/1811.12030) Grid R-CNN [pytorch](https://github.com/STVIR/Grid-R-CNN)\n  - [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)\n  - [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)\n  - [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)\n  - [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)\n  - [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)\n   \n## Recent Papers\n  - [PrROI](https://arxiv.org/pdf/1807.11590.pdf) Acquisition of Localization confidence for accurate object detection ECCV2018\n  - [FreeAnchor](https://arxiv.org/pdf/1909.02466.pdf) FreeAnchor: Learning to Match Anchors for Visual \nObject Detection [pytorch](https://github.com/zhangxiaosong18/FreeAnchor) NIPS2019\n  - [CBNet](https://arxiv.org/pdf/1909.03625.pdf) CBNet: A Novel Composite Backbone Network Architecture for Object Detection\n[caffe2](https://github.com/PKUbahuangliuhe/CBNet) \n  - [CenterNet](https://arxiv.org/pdf/1904.08189.pdf) CenterNet: Keypoint Triplets for Object Detection [pytorch](https://github.com/Duankaiwen/CenterNet)\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/daicoolb%2Fawesome-object-detections/projects"}