Object Localization
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Object Localization is the task of locating an instance of a particular object category in an image, typically by specifying a tightly cropped bounding box centered on the instance. An object proposal specifies a candidate bounding box, and an object proposal is said to be a correct localization if it sufficiently overlaps a human-labeled “ground-truth” bounding box for the given object. In the literature, the “Object Localization” task is to locate one instance of an object category, whereas “object detection” focuses on locating all instances of a category in a given image.
Source: Fast On-Line Kernel Density Estimation for Active Object Localization
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/harrybolingot/mymaskrcnn
https://github.com/hellohaozheng/maskrcnn-mindspore
https://github.com/hh-xiaohu/Image-augementation-pytorch
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/houseleo/pointnet
https://github.com/houssemjebari/Fruit-Detection
https://github.com/hy-signal/VoxelNet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/hysts/pytorch_cutmix
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/hz-ants/cosypose-Base-on-multi-view
https://github.com/ibaiGorordo/ONNX-Object-Localization-Network
Learning Open-World Object Proposals without Learning to Classify
https://github.com/ildoonet/cutmix
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/ilyak93/GAIN-pytorch
https://github.com/infini8-13/MaskRCNN_tryout
https://github.com/innat/ML-Bookmarks
https://github.com/innat/ML-Resource
https://github.com/is2ai/kazparc
https://github.com/itsasimiqbal/SeBRe
https://github.com/jacobgil/pytorch-grad-cam
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
https://github.com/jasjeetIM/Mask-RCNN
https://github.com/jediofgever/PointNet_Custom_Object_Detection
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/jhihan/rsna_pneumonia_detection
https://github.com/jiajunhua/facebookresearch-Detectron
https://github.com/jianing-sun/Mask-YOLO
https://github.com/jiportilla/edge-max-object-detector
https://github.com/jis478/Tensorflow/tree/master/TF2.0/Cutmix
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/jis478/cutmix_tensorflow2
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/jklife3/maskrcnn-impl
https://github.com/joaopauloschuler/k-neural-api
https://github.com/jodumagpi/Xray-ObjSep-v1
https://github.com/joeylitalien/noise2noise-pytorch
https://github.com/jongwoopark7978/LVNet
https://github.com/jooyounghun/AI-Team-5
https://github.com/jremillard/images-to-osm
https://github.com/js-aguiar/wheat-object-detection
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/jsr66/Machine-Learning-Phases-of-Matter-with-Discriminative-Localization
https://github.com/jsr66/Machine-Learning-Phases-of-Matter-with-Discriminative-Localization-
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.