Cover Image

Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Deng, Peihua, Zhang, Jiehua, Sheng, Xichun, Yan, Chenggang, Sun, Yaoqi, Fu, Ying, Li, Liang
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental Learning
by: Yin, Jiong, et al.
Published: (2025)

Few-Shot Generative Model Adaption via Identity Injection and Preservation
by: He, Yeqi, et al.
Published: (2026)

Prototypical Distillation and Debiased Tuning for Black-box Unsupervised Domain Adaptation
by: Liang, Jian, et al.
Published: (2024)

Cross-Domain Attribute Alignment with CLIP: A Rehearsal-Free Approach for Class-Incremental Unsupervised Domain Adaptation
by: Mi, Kerun, et al.
Published: (2025)

Salient Object Detection in Complex Weather Conditions via Noise Indicators
by: Chen, Quan, et al.
Published: (2025)

Progressive Depth Decoupling and Modulating for Flexible Depth Completion
by: Yang, Zhiwen, et al.
Published: (2024)

Data-Free Class-Incremental Gesture Recognition with Prototype-Guided Pseudo Feature Replay
by: Wang, Hongsong, et al.
Published: (2025)

HAM: A Training-Free Style Transfer Approach via Heterogeneous Attention Modulation for Diffusion Models
by: He, Yeqi, et al.
Published: (2026)

Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning
by: Liu, Jiaming, 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-guided Open-Set Source-Free Unsupervised Domain Adaptation with Target-private Class Segregation
by: Litrico, Mattia, et al.
Published: (2024)

A Tale of Two Experts: Cooperative Learning for Source-Free Unsupervised Domain Adaptation
by: Yu, Jiaping, et al.
Published: (2025)

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

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

Rotation Augmented Distillation for Exemplar-Free Class Incremental Learning with Detailed Analysis
by: Chen, Xiuwei, et al.
Published: (2023)

Cluster-Aware Neural Collapse Prompt Tuning for Long-Tailed Generalization of Vision-Language Models
by: Guo, Boyang, et al.
Published: (2026)

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

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

Multi-Source Unsupervised Domain Adaptation with Prototype Aggregation
by: Huang, Min, et al.
Published: (2024)

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

Unlocking Prototype Potential: An Efficient Tuning Framework for Few-Shot Class-Incremental Learning
by: Jiang, Shengqin, et al.
Published: (2026)

Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation
by: Zeng, Hongye, et al.
Published: (2024)

Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning
by: Fukuda, Takuma, et al.
Published: (2024)

First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning
by: Panos, Aristeidis, et al.
Published: (2023)

PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning
by: Ma'sum, Muhammad Anwar, et al.
Published: (2024)

Prototype-Based Pseudo-Label Denoising for Source-Free Domain Adaptation in Remote Sensing Semantic Segmentation
by: Wang, Bin, et al.
Published: (2025)

Attention-based Class-Conditioned Alignment for Multi-Source Domain Adaptation of Object Detectors
by: Belal, Atif, et al.
Published: (2024)

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

Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation
by: Chen, Haoran, et al.
Published: (2022)

Temporal Source Recovery for Time-Series Source-Free Unsupervised Domain Adaptation
by: Wang, Yucheng, et al.
Published: (2024)

Source-Free Unsupervised Domain Adaptation with Hypothesis Consolidation of Prediction Rationale
by: Shu, Yangyang, et al.
Published: (2024)

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

CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning
by: He, Jiangpeng, et al.
Published: (2025)

DATR: Unsupervised Domain Adaptive Detection Transformer with Dataset-Level Adaptation and Prototypical Alignment
by: Han, Jianhong, et al.
Published: (2024)

Beyond Retraining: Training-Free Unknown Class Filtering for Source-Free Open Set Domain Adaptation of Vision-Language Models
by: Li, Yongguang, et al.
Published: (2025)

On the Discrimination and Consistency for Exemplar-Free Class Incremental Learning
by: Wang, Tianqi, et al.
Published: (2025)

Multi-Prompt Progressive Alignment for Multi-Source Unsupervised Domain Adaptation
by: Chen, Haoran, et al.
Published: (2025)

Incremental Pseudo-Labeling for Black-Box Unsupervised Domain Adaptation
by: Zou, Yawen, et al.
Published: (2024)

On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning
by: Fang, Pengfei, et al.
Published: (2024)

Gradient-based Class Weighting for Unsupervised Domain Adaptation in Dense Prediction Visual Tasks
by: Alcover-Couso, Roberto, et al.
Published: (2024)