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Semi Supervised Learning for Image Captioning

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하위 태스크: 1
평가표: 3
보존된 평가 기록: 3

코드

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

https://github.com/cao-cong/ads-semiseg

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Adversarial Dual-Student with Differentiable Spatial Warping for Semi-Supervised Semantic Segmentation

https://github.com/carrotsniper/bp-sgcn

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BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction

https://github.com/chaneyddtt/UDA-Animal-Pose

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From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation

https://github.com/chaneyddtt/scarcenet

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ScarceNet: Animal Pose Estimation with Scarce Annotations

https://github.com/chen-xin-94/dart

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DART: An Automated End-to-End Object Detection Pipeline with Data Diversification, Open-Vocabulary Bounding Box Annotation, Pseudo-Label Review, and Model Training

https://github.com/chenxi52/upa

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Uncertainty-Aware Pseudo-Label Filtering for Source-Free Unsupervised Domain Adaptation

https://github.com/christmasfan/ssl_denoising_segmentation

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Pseudo-Label Noise Suppression Techniques for Semi-Supervised Semantic Segmentation

https://github.com/chu0802/sla

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Semi-Supervised Domain Adaptation with Source Label Adaptation

https://github.com/chumsy0725/fbc-sa

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Towards Generalizing to Unseen Domains with Few Labels

https://github.com/ciampluca/diffusion_semi_supervised_biomedical_image_segmentation

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Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

https://github.com/codegallery24/cpcl

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CPCL: Cross-Modal Prototypical Contrastive Learning for Weakly Supervised Text-based Person Re-Identification

https://github.com/computational-cell-analytics/probabilistic-domain-adaptation

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Probabilistic Domain Adaptation for Biomedical Image Segmentation

https://github.com/contentandmaterialportrait/mae-gebd

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Masked Autoencoders for Generic Event Boundary Detection CVPR'2022 Kinetics-GEBD Challenge

https://github.com/csimo005/summit

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SUMMIT: Source-Free Adaptation of Uni-Modal Models to Multi-Modal Targets

https://github.com/cskyl/sam_wsss

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Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

https://github.com/ctu-vras/t-concord3d

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Teachers in concordance for pseudo-labeling of 3D sequential data

https://github.com/cuhk-aim-group/diffrect

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DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation

https://github.com/cvlab-stonybrook/Weighting-Pseudo-Labels

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Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised Segmentation

https://github.com/cvlab-stonybrook/beyond-pixels

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Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale Patch-based Multi-Label Classifier

https://github.com/czm369/mixpl

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Mixed Pseudo Labels for Semi-Supervised Object Detection

https://github.com/d10andy/sad

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SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs

https://github.com/damo-nlp-sg/contproto

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Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learning

https://github.com/danikiyasseh/SoCal

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SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals

https://github.com/danikiyasseh/SoQal

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SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals

https://github.com/davidhuji/capdec

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Text-Only Training for Image Captioning using Noise-Injected CLIP

https://github.com/ddz16/TSASPC

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Timestamp-Supervised Action Segmentation from the Perspective of Clustering

https://github.com/deceptrax123/jpeb-gssl

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Leveraging Joint Predictive Embedding and Bayesian Inference in Graph Self Supervised Learning

https://github.com/declare-lab/sat

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SAT: Improving Semi-Supervised Text Classification with Simple Instance-Adaptive Self-Training

https://github.com/deepglint/unicom

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Multi-label Cluster Discrimination for Visual Representation Learning

https://github.com/deepmind/semppl

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SemPPL: Predicting pseudo-labels for better contrastive representations

https://github.com/deeptibhegde/attentiveprototypesfuda

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Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection

https://github.com/dheeraj7596/lops

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LOPS: Learning Order Inspired Pseudo-Label Selection for Weakly Supervised Text Classification

https://github.com/dmcv-ecnu/MindSpore_ModelZoo

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Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud

https://github.com/dosowiechi/clipartt

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CLIPArTT: Adaptation of CLIP to New Domains at Test Time

https://github.com/dylan-h-wang/skin-sm3

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Self-Supervised Multi-Modality Learning for Multi-Label Skin Lesion Classification

https://github.com/dymanne123/PLPCL

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Pseudo-Label Enhanced Prototypical Contrastive Learning for Uniformed Intent Discovery

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