class-incremental learning
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Benchmarks
Most implemented
Overcoming catastrophic forgetting in neural networks
iCaRL: Incremental Classifier and Representation Learning
Three scenarios for continual learning
Learning to Prompt for Continual Learning
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches
Large Scale Incremental Learning
Papers
Mitigating Performance Discrepancy in Cross-Domain 3D Class-Incremental Learning
3D perception plays a crucial role in real-world applications such as autonomous driving, robotics, and AR/VR. In practical scenarios, 3D perception models need to continually adapt to newly emerging 3D object categories…
class-incremental learningAutonomous DrivingPoint CloudsKnowing Beyond the Known: Reinforced Knowledge Specification for Multi-Label Class-Incremental Learning
Existing class-incremental learning methods struggle in multi-label scenarios (MLCIL) due to the inherent contradiction of learning objectives arising from co-occurring and incomplete labels. We argue that the core obsta…
class-incremental learningGeo-LoRA: Geometry-Aware Subspace Evolution for Low-Rank Adaptation in Continual Learning
Rehearsal-free class-incremental learning (CIL) with LoRA adapters remains challenging because the low-rank subspaces updated across tasks evolve without geometric control, causing unstable shared representations and rep…
class-incremental learningContinual LearningParameter Efficient Continual Learning for Sparse Event-Based Transformers
Robotic and edge intelligence systems operate in dynamic environments where data arrives continuously, requiring models to adapt while preserving previously learned knowledge under strict memory and energy constraints. W…
parameter-efficient fine-tuningclass-incremental learningContinual LearningEvent-based visionSPARCL: Spectral Partitioned Analytic Continual Learning
Analytic continual learning has emerged as a strong exemplar-free alternative to gradient-based class-incremental learning because it replaces iterative optimization with closed-form ridge updates. Yet the usual forgetti…
class-incremental learningContinual LearningSocialized Division and Collaboration: Rethinking Class-Incremental Learning under Optimization Conflicts
Class-incremental learning is commonly instantiated as a single-model paradigm, where a unified model sequentially adapts to an unbounded stream of sessions. While effective under mild distributional shifts, this formula…
class-incremental learningContinual Learning