Cover Image

Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kong, Heejo, Kim, Sung-Jin, Jung, Gunho, Lee, Seong-Whan
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Text-guided Weakly Supervised Framework for Dynamic Facial Expression Recognition
by: Jung, Gunho, et al.
Published: (2025)

AM-SORT: Adaptable Motion Predictor with Historical Trajectory Embedding for Multi-Object Tracking
by: Kim, Vitaliy, et al.
Published: (2024)

TE-TAD: Towards Full End-to-End Temporal Action Detection via Time-Aligned Coordinate Expression
by: Kim, Ho-Joong, et al.
Published: (2024)

Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning
by: Duan, Yue, et al.
Published: (2025)

CW-BASS: Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic Segmentation
by: Tarubinga, Ebenezer, et al.
Published: (2025)

Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning
by: Yu, Yang, et al.
Published: (2023)

FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation
by: Tarubinga, Ebenezer, et al.
Published: (2025)

RaDL: Relation-aware Disentangled Learning for Multi-Instance Text-to-Image Generation
by: Park, Geon, et al.
Published: (2025)

Dynamic Sub-graph Distillation for Robust Semi-supervised Continual Learning
by: Fan, Yan, et al.
Published: (2023)

Towards Better Visualizing the Decision Basis of Networks via Unfold and Conquer Attribution Guidance
by: Hong, Jung-Ho, et al.
Published: (2023)

Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation
by: Ha, SeungBum, et al.
Published: (2024)

Outlier-Robust Training of Machine Learning Models
by: Talak, Rajat, et al.
Published: (2024)

Meta-Semi: A Meta-learning Approach for Semi-supervised Learning
by: Wang, Yulin, et al.
Published: (2020)

Recent Deep Semi-supervised Learning Approaches and Related Works
by: Kim, Gyeongho
Published: (2021)

Revisiting Semi-supervised Adversarial Robustness via Noise-aware Online Robust Distillation
by: Wu, Tsung-Han, et al.
Published: (2024)

Visualizing the loss landscape of Self-supervised Vision Transformer
by: Lee, Youngwan, et al.
Published: (2024)

Understanding Flatness in Generative Models: Its Role and Benefits
by: Lee, Taehwan, et al.
Published: (2025)

DQE-CIR: Distinctive Query Embeddings through Learnable Attribute Weights and Target Relative Negative Sampling in Composed Image Retrieval
by: Park, Geon, et al.
Published: (2026)

RelationMatch: Matching In-batch Relationships for Semi-supervised Learning
by: Zhang, Yifan, et al.
Published: (2023)

Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data
by: Roy, Shuvendu, et al.
Published: (2023)

Do not trust what you trust: Miscalibration in Semi-supervised Learning
by: Mishra, Shambhavi, et al.
Published: (2024)

Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness
by: Landgraf, Steven, et al.
Published: (2025)

Simple yet Effective Semi-supervised Knowledge Distillation from Vision-Language Models via Dual-Head Optimization
by: Kang, Seongjae, et al.
Published: (2025)

Rethinking Open-World Semi-Supervised Learning: Distribution Mismatch and Inductive Inference
by: Park, Seongheon, et al.
Published: (2024)

Analyzing Effects of Mixed Sample Data Augmentation on Model Interpretability
by: Won, Soyoun, et al.
Published: (2023)

VCC-INFUSE: Towards Accurate and Efficient Selection of Unlabeled Examples in Semi-supervised Learning
by: Fang, Shijie, et al.
Published: (2024)

Location-based Radiology Report-Guided Semi-supervised Learning for Prostate Cancer Detection
by: Chen, Alex, et al.
Published: (2024)

Neighbor Does Matter: Density-Aware Contrastive Learning for Medical Semi-supervised Segmentation
by: Tang, Feilong, et al.
Published: (2024)

Flexible Distribution Alignment: Towards Long-tailed Semi-supervised Learning with Proper Calibration
by: Aimar, Emanuel Sanchez, et al.
Published: (2023)

BaCon: Boosting Imbalanced Semi-supervised Learning via Balanced Feature-Level Contrastive Learning
by: Feng, Qianhan, et al.
Published: (2024)

EOL: Transductive Few-Shot Open-Set Recognition by Enhancing Outlier Logits
by: Ochal, Mateusz, et al.
Published: (2024)

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization
by: Huang, Yongle, et al.
Published: (2025)

Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach
by: Cao, Jinzhou, et al.
Published: (2025)

Robust Data Clustering with Outliers via Transformed Tensor Low-Rank Representation
by: Wu, Tong
Published: (2023)

RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples
by: Mirzaei, Hossein, et al.
Published: (2025)

SCOMatch: Alleviating Overtrusting in Open-set Semi-supervised Learning
by: Wang, Zerun, et al.
Published: (2024)

Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning
by: Ye, Bo, et al.
Published: (2023)

Weakly Semi-supervised Tool Detection in Minimally Invasive Surgery Videos
by: Fujii, Ryo, et al.
Published: (2024)

Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling
by: Lin, Hui, et al.
Published: (2024)

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization
by: Lee, Dongyeun, et al.
Published: (2025)