Object Localization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 18
- 보존된 평가 기록
- 51
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/yangyucheng000/maskrcnn_mobilenetv1
https://github.com/yanx27/Pointnet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/yashdani/Object-Detection-Using-YOLOv3-Algorithm
https://github.com/yczhang1017/SSD_resnet_pytorch
https://github.com/yeezhu/SPN.pytorch
Soft Proposal Networks for Weakly Supervised Object Localization
https://github.com/yiskw713/ClassActivationMapping
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
https://github.com/yiskw713/SmoothGradCAMplusplus
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
https://github.com/yiskw713/scorecam
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
https://github.com/yj-littlesky/py-faster-rcnn
https://github.com/ykasten/layered-neural-atlases
https://github.com/ylabbe/cosypose
https://github.com/ytng001/sensemaking
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/yubaoliu/rds-slam
https://github.com/yuhaonankaka/adl_maskrcnn
ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
https://github.com/yuhsijen/Object-Detector
https://github.com/yui-mhcp/base_dl_project
https://github.com/yukitsuji/chainer_function
https://github.com/yunqing-me/attackvlm
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
https://github.com/yxgeee/SFRS
Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
https://github.com/yxgeee/openibl
Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
https://github.com/zdcuob/Fully-Convlutional-Neural-Networks-for-state-of-the-art-time-series-classification-
https://github.com/zenroad/modifypointnet
https://github.com/zgx0534/pointnet_win
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/zhangchi9/Airbus_Ship_Detection
https://github.com/zhengshou/AutoLoc
https://github.com/zhihaozhang97/ru-ai
https://github.com/zhong110020/py-faster-rcnn
https://github.com/zphang/saliency_investigation
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets
https://gitlab.com/Percipiote/skelda
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.