:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Yao, Yifei, Zhang, Hanrong
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2409.07757
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning
by: Zheng, Bowen, et al.
Published: (2025)

PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning
by: Guo, Haiyang, et al.
Published: (2024)

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

From Events to Clarity: The Event-Guided Diffusion Framework for Dehazing
by: Wang, Ling, et al.
Published: (2025)

Semantic-Guided Dynamic Sparsification for Pre-Trained Model-based Class-Incremental Learning
by: Liu, Ruiqi, et al.
Published: (2026)

Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning
by: Wu, Fangwen, et al.
Published: (2025)

IPSeg: Image Posterior Mitigates Semantic Drift in Class-Incremental Segmentation
by: Yu, Xiao, et al.
Published: (2025)

Exemplar-Free Class Incremental Learning via Incremental Representation
by: Huang, Libo, et al.
Published: (2024)

Feature Expansion and enhanced Compression for Class Incremental Learning
by: Ferdinand, Quentin, et al.
Published: (2024)

Instance-wise Uncertainty for Class Imbalance in Semantic Segmentation
by: Almeida, Luís, et al.
Published: (2024)

ESSENTIAL: Episodic and Semantic Memory Integration for Video Class-Incremental Learning
by: Lee, Jongseo, et al.
Published: (2025)

SAGI: Semantically Aligned and Uncertainty Guided AI Image Inpainting
by: Giakoumoglou, Paschalis, et al.
Published: (2025)

DiffClass: Diffusion-Based Class Incremental Learning
by: Meng, Zichong, et al.
Published: (2024)

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes
by: Hoche, Joseph, et al.
Published: (2025)

CLFSeg: A Fuzzy-Logic based Solution for Boundary Clarity and Uncertainty Reduction in Medical Image Segmentation
by: Kaushal, Anshul, et al.
Published: (2025)

Adaptive Margin Global Classifier for Exemplar-Free Class-Incremental Learning
by: Yao, Zhongren, et al.
Published: (2024)

Mitigating Background Shift in Class-Incremental Semantic Segmentation
by: Park, Gilhan, et al.
Published: (2024)

Adaptive Prototype Replay for Class Incremental Semantic Segmentation
by: Zhu, Guilin, et al.
Published: (2024)

CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning
by: Gao, Xinyuan, et al.
Published: (2024)

Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation
by: Kwak, Jihwan, et al.
Published: (2024)

Class-Independent Increment: An Efficient Approach for Multi-label Class-Incremental Learning
by: Ding, Chenhao, et al.
Published: (2025)

Learning Yourself: Class-Incremental Semantic Segmentation with Language-Inspired Bootstrapped Disentanglement
by: Wu, Ruitao, et al.
Published: (2025)

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

Uncertainty and Energy based Loss Guided Semi-Supervised Semantic Segmentation
by: Thakur, Rini Smita, et al.
Published: (2025)

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

MorphoSeg: An Uncertainty-Aware Deep Learning Method for Biomedical Segmentation of Complex Cellular Morphologies
by: Zhang, Tianhao, et al.
Published: (2024)

Cross-Sample Relational Fusion: Unifying Domain Generalization and Class-Incremental Learning
by: Xie, Zhen-Hao, et al.
Published: (2026)

Background Adaptation with Residual Modeling for Exemplar-Free Class-Incremental Semantic Segmentation
by: Zhang, Anqi, et al.
Published: (2024)

Dynamic Feature Learning and Matching for Class-Incremental Learning
by: Qiang, Sunyuan, et al.
Published: (2024)

Uncertainty-Aware Trajectory Prediction: A Unified Framework Harnessing Positional and Semantic Uncertainties
by: Sun, Jintao, et al.
Published: (2026)

Class Balance Matters to Active Class-Incremental Learning
by: Huang, Zitong, et al.
Published: (2024)

Class Incremental Medical Image Segmentation via Prototype-Guided Calibration and Dual-Aligned Distillation
by: Zhu, Shengqian, et al.
Published: (2025)

Uncertainty-Based Ensemble Learning in CMR Semantic Segmentation
by: Liu, Yiwei, et al.
Published: (2025)

Uncertainty-aware Sampling for Long-tailed Semi-supervised Learning
by: Yang, Kuo, et al.
Published: (2024)

GPS: Distilling Compact Memories via Grid-based Patch Sampling for Efficient Online Class-Incremental Learning
by: Ma, Mingchuan, et al.
Published: (2025)

Reduction of Class Activation Uncertainty with Background Information
by: Kabir, H M Dipu
Published: (2023)

SUG-Occ: Explicit Semantics and Uncertainty Guided Sparse Learning for Efficient 3D Occupancy Prediction
by: Wu, Hanlin, et al.
Published: (2026)

FeTT: Continual Class Incremental Learning via Feature Transformation Tuning
by: Qiang, Sunyuan, et al.
Published: (2024)

Semantic and Feature Guided Uncertainty Quantification of Visual Localization for Autonomous Vehicles
by: Wu, Qiyuan, et al.
Published: (2025)

Hierarchical Semantic Tree Anchoring for CLIP-Based Class-Incremental Learning
by: Hu, Tao, et al.
Published: (2025)