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/Vonski/wdi19
Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video
https://github.com/Westlake-AI/openmixup
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/WordBearerYI/VoxelNet-pytorch
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/YanLiqi/HAF
Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
https://github.com/Yang2446/pointnet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/YangtaoWANG95/TokenCut
Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut
https://github.com/Yc174/frustum-pointnets
https://github.com/YiruS/pointnet_adversarial
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/ZQPei/deep_sort_pytorch
https://github.com/ZhihaoZhu/PointNet-Implementation-Tensorflow
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/aaronfriedman6/MV3D_VoxelNet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/abdullahozer11/Segmentation-and-Classification-of-Objects-in-Point-Clouds
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/ahmdtaha/constrained_attention_filter
A Generic Visualization Approach for Convolutional Neural Networks
https://github.com/ahmed-anas/thesis-pointnet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/ahmedssabir/textual-visual-semantic-dataset
https://github.com/airalcorn2/strike-with-a-pose
https://github.com/airplane2230/keras_cutmix
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/alexalm4190/Mask_RCNN-Vizzy_Hand
https://github.com/alexander-pv/maskrcnn_tf2
https://github.com/alililia/ascend_maskrcnn_mobilenetv1
https://github.com/alililia/gpu_maskrcnn_mobilenetv1
https://github.com/alpemek/ais3d
https://github.com/anshulpaigwar/Frustum-Pointpillars
https://github.com/arbaza/3D-object-detection-KITTI
https://github.com/arnab39/equiadapt
https://github.com/asyrovprog/cs230project
https://github.com/atharv6/Image-Captioning
https://github.com/author31/scm_nbdev
Weakly Supervised Object Localization via Transformer with Implicit Spatial Calibration
https://github.com/aviros/pointnet_totations
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/aviros/roatationPointnet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/ayoolaolafenwa/PixelLib
https://github.com/azad96/cosypose-custom
https://github.com/baodi23/hourglass-facekeypoints-detection
https://github.com/bcmi/phdnet-painterly-image-harmonization
https://github.com/beassssry/U
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.