Papers with Code 아카이브
Weakly-Supervised Object Localization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 7
- 보존된 평가 기록
- 30
Weakly supervised object localization (WSOL) learns to localize objects with only image-level labels, no object level labels (bonding boxes, etc.,) is needed. It is more attractive since image-level labels are much easier and cheaper to obtain.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/TooTouch/WhiteBox-Part1
https://github.com/YangtaoWANG95/TokenCut
Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut
https://github.com/ahmdtaha/constrained_attention_filter
A Generic Visualization Approach for Convolutional Neural Networks
https://github.com/airalcorn2/strike-with-a-pose
https://github.com/author31/scm_nbdev
Weakly Supervised Object Localization via Transformer with Implicit Spatial Calibration
https://github.com/cauchyturing/UCR_Time_Series_Classification_Deep_Learning_Baseline
https://github.com/chandrakantkhandelwal/PracticeCodes
https://github.com/cpuimage/DualAttentionGuidedDropout
Dual-attention Guided Dropblock Module for Weakly Supervised Object Localization
https://github.com/cvi-szu/clims
https://github.com/djib2011/high-res-mapping
https://github.com/fatLime/Predict-Lung-Disease
https://github.com/frgfm/torch-cam
https://github.com/froggydisk/CAM
https://github.com/goddoe/hide-and-seek
https://github.com/innat/ML-Bookmarks
https://github.com/innat/ML-Resource
https://github.com/jacobgil/pytorch-grad-cam
https://github.com/joaopauloschuler/k-neural-api
https://github.com/jsr66/Machine-Learning-Phases-of-Matter-with-Discriminative-Localization
https://github.com/jsr66/Machine-Learning-Phases-of-Matter-with-Discriminative-Localization-
https://github.com/junkwhinger/adversarial_complementary_learning
Adversarial Complementary Learning for Weakly Supervised Object Localization
https://github.com/junsukchoe/ADL
Attention-based Dropout Layer for Weakly Supervised Object Localization
https://github.com/ldjlammers/Hide-and-Seek-CS4240
https://github.com/lukemelas/deep-spectral-segmentation
Localizing Objects with Self-Supervised Transformers and no Labels
https://github.com/metalbubble/CAM
https://github.com/mikuhatsune/dap
https://github.com/pasrichashivam/Convnets_Grad-CAM_Grad-CAM-PlusPlus_Keras_tensorflow-2
https://github.com/philipperemy/tensorflow-class-activation-mapping
https://github.com/sauravmishra1710/EXPLAINABLE-AI---Skin-Cancer-Detection-explained-with-GRADCAM
https://github.com/schizop/SA
https://github.com/shyhyawJou/Eigen-CAM-Tensorflow
https://github.com/shyhyawJou/EigenCAM-Pytorch
https://github.com/teang1995/CAM-Class-Activation-Map-
https://github.com/tensorpack/tensorpack/tree/master/examples/Saliency
https://github.com/timho102003/Background-Aware-CAM-WSOL
Background-aware Classification Activation Map for Weakly Supervised Object Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.