"class-incremental learning" Papers
35 papers found
Conference
Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental Learning
Haoran Chen, Ping Wang, Zihan Zhou et al.
Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning
Takuma Fukuda, Hiroshi Kera, Kazuhiko Kawamoto
AnaCP: Toward Upper-Bound Continual Learning via Analytic Contrastive Projection
Saleh Momeni, Changnan Xiao, Bing Liu
Class-wise Balancing Data Replay for Federated Class-Incremental Learning
Zhuang Qi, Ying-Peng Tang, Lei Meng et al.
CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning
Jiangpeng He, Zhihao Duan, Fengqing Zhu
Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.
Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning
Xusheng Cao, Haori Lu, Linlan Huang et al.
Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning
Wei Chen, Yi Zhou
MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification
Jimin Park, AHyun Ji, Minji Park et al.
Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning
Linlan Huang, Xusheng Cao, Haori Lu et al.
MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao et al.
Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation
Peihua Deng, Jiehua Zhang, Xichun Sheng et al.
PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning
Yongchun Qin, Pengfei Fang, Hui Xue
RainbowPrompt: Diversity-Enhanced Prompt-Evolving for Continual Learning
Kiseong Hong, Gyeong-Hyeon Kim, Eunwoo Kim
Rebalancing Multi-Label Class-Incremental Learning
Kaile Du, Yifan Zhou, Fan Lyu et al.
Seeing 3D Through 2D Lenses: 3D Few-Shot Class-Incremental Learning via Cross-Modal Geometric Rectification
Tuo Xiang, Xuemiao Xu, Bangzhen Liu et al.
Specifying What You Know or Not for Multi-Label Class-Incremental Learning
Aoting Zhang, Dongbao Yang, Chang Liu et al.
Task-Agnostic Guided Feature Expansion for Class-Incremental Learning
Bowen Zheng, Da-Wei Zhou, Han-Jia Ye et al.
T-CIL: Temperature Scaling using Adversarial Perturbation for Calibration in Class-Incremental Learning
Seong-Hyeon Hwang, Minsu Kim, Steven Euijong Whang
Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning
Juntae Lee, Munawar Hayat, Sungrack Yun
Adaptive Discovering and Merging for Incremental Novel Class Discovery
Guangyao Chen, Peixi Peng, Yangru Huang et al.
Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion
Linlan Huang, Xusheng Cao, Haori Lu et al.
CLEO: Continual Learning of Evolving Ontologies
Shishir Muralidhara, Saqib Bukhari, Georg Dr. Schneider et al.
CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning
Junghun Oh, Sungyong Baik, Kyoung Mu Lee
Compositional Few-Shot Class-Incremental Learning
Yixiong Zou, Shanghang Zhang, haichen zhou et al.
DS-AL: A Dual-Stream Analytic Learning for Exemplar-Free Class-Incremental Learning
Huiping Zhuang, Run He, Kai Tong et al.
Exemplar-free Continual Representation Learning via Learnable Drift Compensation
Alex Gomez-Villa, Dipam Goswami, Kai Wang et al.
Generative Multi-modal Models are Good Class Incremental Learners
Xusheng Cao, Haori Lu, Linlan Huang et al.
Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning
Depeng Li, Tianqi Wang, Junwei Chen et al.
Learning to Prompt Knowledge Transfer for Open-World Continual Learning
Yujie Li, Xin Yang, Hao Wang et al.
Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning
Bowen Zheng, Da-Wei Zhou, Han-Jia Ye et al.
Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement
Fushuo Huo, Wenchao Xu, Jingcai Guo et al.
One-stage Prompt-based Continual Learning
Youngeun Kim, YUHANG LI, Priyadarshini Panda
On the Approximation Risk of Few-Shot Class-Incremental Learning
Xuan Wang, Zhong Ji, Xiyao Liu et al.
PromptFusion: Decoupling Stability and Plasticity for Continual Learning
Haoran Chen, Zuxuan Wu, Xintong Han et al.