Cover Image

CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Oh, Junghun, Baik, Sungyong, Lee, Kyoung Mu
Format:	Preprint
Published:	2024
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

MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance Fields
by: Chung, Jaeyoung, et al.
Published: (2022)

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

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

Knowledge Adaptation Network for Few-Shot Class-Incremental Learning
by: Wang, Ye, et al.
Published: (2024)

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

Find A Winning Sign: Sign Is All We Need to Win the Lottery
by: Oh, Junghun, et al.
Published: (2025)

Learn by Reasoning: Analogical Weight Generation for Few-Shot Class-Incremental Learning
by: Han, Jizhou, et al.
Published: (2025)

BiasEdit: A Training-Free Bias-Detect-and-Edit Framework for Learning Fair Visual Classifiers
by: Seo, Jungwook, et al.
Published: (2026)

LAN: Learning to Adapt Noise for Image Denoising
by: Kim, Changjin, et al.
Published: (2024)

CD^2: Constrained Dataset Distillation for Few-Shot Class-Incremental Learning
by: Bao, Kexin, et al.
Published: (2026)

Divide and Conquer: Static-Dynamic Collaboration for Few-Shot Class-Incremental Learning
by: Bao, Kexin, et al.
Published: (2026)

Hyperbolic Coarse-to-Fine Few-Shot Class-Incremental Learning
by: Dai, Jiaxin, et al.
Published: (2025)

Controllable Forgetting Mechanism for Few-Shot Class-Incremental Learning
by: Paramonov, Kirill, et al.
Published: (2025)

Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning
by: Park, Min-Yeong, et al.
Published: (2024)

Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning
by: Zhou, Haichen, et al.
Published: (2024)

PKI: Prior Knowledge-Infused Neural Network for Few-Shot Class-Incremental Learning
by: Baoa, Kexin, et al.
Published: (2026)

MoTiC: Momentum Tightness and Contrast for Few-Shot Class-Incremental Learning
by: He, Zeyu, et al.
Published: (2025)

Beyond Synthetic Replays: Turning Diffusion Features into Few-Shot Class-Incremental Learning Knowledge
by: Kim, Junsu, et al.
Published: (2025)

Can Synthetic Images Conquer Forgetting? Beyond Unexplored Doubts in Few-Shot Class-Incremental Learning
by: Kim, Junsu, et al.
Published: (2025)

Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt
by: Liu, Chenxi, et al.
Published: (2024)

Rethinking RGB Color Representation for Image Restoration Models
by: Lee, Jaerin, et al.
Published: (2024)

Covariance-based Space Regularization for Few-shot Class Incremental Learning
by: Hu, Yijie, et al.
Published: (2024)

Anomaly as Non-Conformity via Training-Free Graph Laplacian Energy Minimization
by: Seo, Jungwook, et al.
Published: (2026)

MatRes: Zero-Shot Test-Time Model Adaptation for Simultaneous Matching and Restoration
by: Lee, Kanggeon, et al.
Published: (2026)

Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss
by: Kim, Jaeha, et al.
Published: (2024)

Exploiting Diffusion Prior for Task-driven Image Restoration
by: Kim, Jaeha, et al.
Published: (2025)

Few-shot Class-Incremental Learning via Generative Co-Memory Regularization
by: Bao, Kexin, et al.
Published: (2026)

Latest Advancements Towards Catastrophic Forgetting under Data Scarcity: A Comprehensive Survey on Few-Shot Class Incremental Learning
by: Ma'sum, M. Anwar, et al.
Published: (2025)

Hierarchical Representation Matching for CLIP-based Class-Incremental Learning
by: Wen, Zhen-Hao, et al.
Published: (2025)

Bidirectional Multimodal Prompt Learning with Scale-Aware Training for Few-Shot Multi-Class Anomaly Detection
by: Lee, Yujin, 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)

Completely Weakly Supervised Class-Incremental Learning for Semantic Segmentation
by: Kim, David Minkwan, et al.
Published: (2025)

Federated Class-Incremental Learning with Prompting
by: Luo, Xin, et al.
Published: (2023)

Representation Calibration and Uncertainty Guidance for Class-Incremental Learning based on Vision Language Model
by: Tan, Jiantao, et al.
Published: (2025)

Feature-Space Generative Models for One-Shot Class-Incremental Learning
by: Foster, Jack, et al.
Published: (2026)

STAR: Semantic-Temporal Adaptive Representation Learning for Few-Shot Action Recognition
by: Liu, Hongli, et al.
Published: (2026)

DeClotH: Decomposable 3D Cloth and Human Body Reconstruction from a Single Image
by: Nam, Hyeongjin, et al.
Published: (2025)

Unlocking Transfer Learning for Open-World Few-Shot Recognition
by: Kim, Byeonggeun, et al.
Published: (2024)

Mutually-Aware Feature Learning for Few-Shot Object Counting
by: Jeon, Yerim, et al.
Published: (2024)

Depth-Regularized Optimization for 3D Gaussian Splatting in Few-Shot Images
by: Chung, Jaeyoung, et al.
Published: (2023)