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Weakly-supervised Learning

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/tu-delft-ai-energy-lab/deep-statistical-solver-for-distribution-system-state-estimation

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Deep Statistical Solver for Distribution System State Estimation

https://github.com/tunazislam/weaklysup-fb-ad-political

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Weakly Supervised Learning for Analyzing Political Campaigns on Facebook

https://github.com/ucla-starai/countloss

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A Unified Approach to Count-Based Weakly-Supervised Learning

https://github.com/uds-lsv/critical_wsl

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Weaker Than You Think: A Critical Look at Weakly Supervised Learning

https://github.com/ut21/wsad-driving

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What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised Horizon

https://github.com/vinairesearch/single_image_hdr

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Single-Image HDR Reconstruction by Multi-Exposure Generation

https://github.com/vison307/hisynseg

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HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization

https://github.com/vita-epfl/FG2

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FG$^2$: Fine-Grained Cross-View Localization by Fine-Grained Feature Matching

https://github.com/vru2020/Pose_3D

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Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry

https://github.com/weiguangzhao/df_mvr

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From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion

https://github.com/wilsonmqz/ltrl

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Learning from Reduced Labels for Long-Tailed Data

https://github.com/wu-zhonghua/rac-net

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Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud Segmentation

https://github.com/wuyongjiancode/cyclic

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Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation

https://github.com/wwangwitsel/scarce

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Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical

https://github.com/xiaoaoran/3d_label_efficient_learning

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A Survey of Label-Efficient Deep Learning for 3D Point Clouds

https://github.com/xuez-phd/efficient-rgb-t-early-fusion-detection

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Rethinking Early-Fusion Strategies for Improved Multispectral Object Detection

https://github.com/xyt-ml/plc

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Partial Label Clustering

https://github.com/yfqiu-nlp/vlm-world-model

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Bootstrapping World Models from Dynamics Models in Multimodal Foundation Models

https://github.com/yichiac/crop-type-transfer-learning

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On the Generalizability of Foundation Models for Crop Type Mapping

https://github.com/yitongli123/isc-te

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Scribble-Supervised Target Extraction Method Based on Inner Structure-Constraint for Remote Sensing Images

https://github.com/yolu1055/weakly-supervised-label-learning-flow

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Weakly Supervised Label Learning Flows

https://github.com/youngfly11/ReIR-WeaklyGrounding.pytorch

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Relation-aware Instance Refinement for Weakly Supervised Visual Grounding

https://github.com/yuexin18/morseg-cam-sam

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Morphology-Enhanced CAM-Guided SAM for weakly supervised Breast Lesion Segmentation

https://github.com/yujiaoshi/g2sweakly

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Weakly-supervised Camera Localization by Ground-to-satellite Image Registration

https://github.com/yyjmjc/temporal-emotion-localization-in-videos

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Dilated Context Integrated Network with Cross-Modal Consensus for Temporal Emotion Localization in Videos

https://github.com/zeroqiaoba/irnet

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IRNet: Iterative Refinement Network for Noisy Partial Label Learning

https://github.com/zgojcic/Rigid3DSceneFlow

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Weakly Supervised Learning of Rigid 3D Scene Flow

https://github.com/zhangz7112/pva-cas

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Partial Vessels Annotation-based Coronary Artery Segmentation with Self-training and Prototype Learning

https://github.com/zhenghuizhao/transwcd

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Exploring Effective Priors and Efficient Models for Weakly-Supervised Change Detection

https://github.com/ziyangwang007/mamba-unet

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Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentation

https://gitlab.lrz.de/compai/MediastinalLymphNodeSegmentation

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Mask the Unknown: Assessing Different Strategies to Handle Weak Annotations in the MICCAI2023 Mediastinal Lymph Node Quantification Challenge

https://gitlab.oit.duke.edu/railabs/LoGroup/multi-label-weakly-supervised-classification-of-body-ct

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What limits performance of weakly supervised deep learning for chest CT classification?

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