https://github.com/shakeebmurtaza/TrCAM
공식 코드Leveraging Transformers for Weakly Supervised Object Localization in Unconstrained Videos
Papers with Code 아카이브
Weakly-Supervised Object Localization
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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/shakeebmurtaza/dips
공식 코드https://github.com/shakeebmurtaza/tedloc
공식 코드TeD-Loc: Text Distillation for Weakly Supervised Object Localization
https://github.com/shakeebmurtaza/wsol_model_selection
공식 코드A Realistic Protocol for Evaluation of Weakly Supervised Object Localization
https://github.com/shantanuj/tdam_top_down_attention_module
공식 코드TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs
https://github.com/shaofeifei11/CI-CAM
공식 코드Improving Weakly-supervised Object Localization via Causal Intervention
https://github.com/shaofeifei11/kd-ci-cam
공식 코드Knowledge-guided Causal Intervention for Weakly-supervised Object Localization
https://github.com/snskysk/cam-back-again
공식 코드CAM Back Again: Large Kernel CNNs from a Weakly Supervised Object Localization Perspective
https://github.com/su-hui-zz/reattentiontransformer
공식 코드Re-Attention Transformer for Weakly Supervised Object Localization
https://github.com/tzzcl/PSOL
공식 코드Rethinking the Route Towards Weakly Supervised Object Localization
https://github.com/valeoai/LOST
공식 코드Localizing Objects with Self-Supervised Transformers and no Labels
https://github.com/vasgaowei/TS-CAM
공식 코드TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization
https://github.com/visipedia/inat_loc
공식 코드https://github.com/weijun88/SPOL
공식 코드Shallow Feature Matters for Weakly Supervised Object Localization
https://github.com/wpy1999/bas
공식 코드Background Activation Suppression for Weakly Supervised Object Localization
https://github.com/wpy1999/bas-extension
공식 코드https://github.com/wpy1999/sat
공식 코드Spatial-Aware Token for Weakly Supervised Object Localization
https://github.com/xiaomengyc/SEM
공식 코드Rethinking Localization Map: Towards Accurate Object Perception with Self-Enhancement Maps
https://github.com/xiaomengyc/SPG
공식 코드Self-produced Guidance for Weakly-supervised Object Localization
https://github.com/zh460045050/bagcams
공식 코드Bagging Regional Classification Activation Maps for Weakly Supervised Object Localization
https://github.com/zh460045050/da-wsol_cvpr2022
공식 코드https://github.com/zhoubolei/CAM
공식 코드https://github.com/Azure/AzureChestXRay
https://github.com/FrancescoSaverioZuppichini/A-journey-into-Convolutional-Neural-Network-visualization-
https://github.com/GenDisc/IVR
Evaluating Weakly Supervised Object Localization Methods Right
https://github.com/GoAhead106283/MURA_deep_learning
https://github.com/HRanWang/SA
https://github.com/HRanWang/Spatial-Attention
https://github.com/HRanWang/Spatial-Re-Scaling
https://github.com/Hayashi-Yudai/ML_models
Adversarial Complementary Learning for Weakly Supervised Object Localization
https://github.com/HichemDebbi/CexCNN
https://github.com/KangBK0120/CAM
https://github.com/MarcBS/keras
https://github.com/MinSongKi/InCA.github.io
In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object Localization
https://github.com/Seb-Good/deep_ecg
https://github.com/Seb-Good/deepecg
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.