Cover Image

SPARSE Data, Rich Results: Few-Shot Semi-Supervised Learning via Class-Conditioned Image Translation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Manni, Guido, Lauretti, Clemente, Zollo, Loredana, Soda, Paolo
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BodySLAM: A Generalized Monocular Visual SLAM Framework for Surgical Applications
by: Manni, G., et al.
Published: (2024)

Semantic-Anchored, Class Variance-Optimized Clustering for Robust Semi-Supervised Few-Shot Learning
by: Maji, Souvik, et al.
Published: (2025)

Ambiguity-Guided Learnable Distribution Calibration for Semi-Supervised Few-Shot Class-Incremental Learning
by: Lyu, Fan, et al.
Published: (2025)

A Strong Baseline for Semi-Supervised Incremental Few-Shot Learning
by: Zhao, Linglan, et al.
Published: (2021)

GCT: Graph Co-Training for Semi-Supervised Few-Shot Learning
by: Xu, Rui, et al.
Published: (2022)

Semi-Supervised Few-Shot Adaptation of Vision-Language Models
by: Silva-Rodríguez, Julio, et al.
Published: (2026)

Breaking Forgetting: Training-Free Few-Shot Class-Incremental Learning via Conditional Diffusion
by: Kang, Haidong, et al.
Published: (2025)

Pseudo-Labeling Based Practical Semi-Supervised Meta-Training for Few-Shot Learning
by: Dong, Xingping, et al.
Published: (2022)

Learning to Obstruct Few-Shot Image Classification over Restricted Classes
by: Zheng, Amber Yijia, et al.
Published: (2024)

Solving Semi-Supervised Few-Shot Learning from an Auto-Annotation Perspective
by: Liu, Tian, et al.
Published: (2025)

Sample-Aware Test-Time Adaptation for Medical Image-to-Image Translation
by: Iele, Irene, et al.
Published: (2025)

Enhanced Few-Shot Class-Incremental Learning via Ensemble Models
by: Zhu, Mingli, et al.
Published: (2024)

SPRINT: Semi-supervised Prototypical Representation for Few-Shot Class-Incremental Tabular Learning
by: Suleymanov, Umid, et al.
Published: (2026)

Spectral-Spatial Self-Supervised Learning for Few-Shot Hyperspectral Image Classification
by: Chen, Wenchen, et al.
Published: (2025)

Few-Shot Learning with Class Imbalance
by: Ochal, Mateusz, et al.
Published: (2021)

Bias Mitigating Few-Shot Class-Incremental Learning
by: Zhao, Li-Jun, et al.
Published: (2024)

Semantic Class Distribution Learning for Debiasing Semi-Supervised Medical Image Segmentation
by: Su, Yingxue, et al.
Published: (2026)

Class-relevant Patch Embedding Selection for Few-Shot Image Classification
by: Jiang, Weihao, et al.
Published: (2024)

Controllable Relation Disentanglement for Few-Shot Class-Incremental Learning
by: Zhou, Yuan, et al.
Published: (2024)

Adaptive Decision Boundary for Few-Shot Class-Incremental Learning
by: Li, Linhao, et al.
Published: (2025)

Active Self-Semi-Supervised Learning for Few Labeled Samples
by: Wen, Ziting, et al.
Published: (2022)

Few-Shot Image Generation by Conditional Relaxing Diffusion Inversion
by: Cao, Yu, et al.
Published: (2024)

Compositional Few-Shot Class-Incremental Learning
by: Zou, Yixiong, et al.
Published: (2024)

Strategic Base Representation Learning via Feature Augmentations for Few-Shot Class Incremental Learning
by: Nema, Parinita, et al.
Published: (2025)

LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object Detection
by: Tran, Phi Vu
Published: (2023)

CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning
by: Liu, Chengyan, et al.
Published: (2024)

Singular Value Fine-tuning for Few-Shot Class-Incremental Learning
by: Wang, Zhiwu, et al.
Published: (2025)

Conditional Distribution Modelling for Few-Shot Image Synthesis with Diffusion Models
by: Gupta, Parul, et al.
Published: (2024)

Segment Any Class (SAC): Multi-Class Few-Shot Semantic Segmentation via Class Region Proposals
by: Zakir, Hussni Mohd, et al.
Published: (2024)

Towards Non-Exemplar Semi-Supervised Class-Incremental Learning
by: Liu, Wenzhuo, et al.
Published: (2024)

Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision
by: Gaillochet, Mélanie, et al.
Published: (2024)

CDMAD: Class-Distribution-Mismatch-Aware Debiasing for Class-Imbalanced Semi-Supervised Learning
by: Lee, Hyuck, et al.
Published: (2024)

Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation
by: Zhang, Yumin, et al.
Published: (2024)

OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental Learning
by: Ahmed, Noor, et al.
Published: (2024)

Learning Prompt with Distribution-Based Feature Replay for Few-Shot Class-Incremental Learning
by: Huang, Zitong, et al.
Published: (2024)

PL-FSCIL: Harnessing the Power of Prompts for Few-Shot Class-Incremental Learning
by: Tian, Songsong, et al.
Published: (2024)

Few-Shot Class-Incremental Learning For Efficient SAR Automatic Target Recognition
by: Karantaidis, George, et al.
Published: (2025)

DINOv2 based Self Supervised Learning For Few Shot Medical Image Segmentation
by: Ayzenberg, Lev, et al.
Published: (2024)

Learning Robust Correlation with Foundation Model for Weakly-Supervised Few-Shot Segmentation
by: Huang, Xinyang, et al.
Published: (2024)

Multimodal Parameter-Efficient Few-Shot Class Incremental Learning
by: D'Alessandro, Marco, et al.
Published: (2023)