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cs.LG2025
Multi-level Collaborative Distillation Meets Global Workspace Model: A Unified Framework for OCIL
Shibin Su, Guoqiang Liang, De Cheng +2
Online Class-Incremental Learning (OCIL) enables models to learn continuously from non-i.i.d. data streams. Since samples of the data streams can be seen only once, it is more suit…
cs.CV2025
Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation
Lingyan Ran, Yali Li, Tao Zhuo +2
In semi-supervised semantic segmentation (SSSS), data augmentation plays a crucial role in the weak-to-strong consistency regularization framework, as it enhances diversity and imp…
cs.CV2025
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector
Qirui Wu, Shizhou Zhang, De Cheng +4
Catastrophic forgetting is a critical chanllenge for incremental object detection (IOD). Most existing methods treat the detector monolithically, relying on instance replay or know…