SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection

arXiv:2402.17323v1 Announce Type: new
Abstract: In the field of class incremental learning (CIL), genera- tive replay has become increasingly prominent as a method to mitigate the catastrophic forgetting, alongside the con- tinuous improvements in generative models. However, its application in class incremental object detection (CIOD) has been significantly limited, primarily due to the com- plexities of scenes involving multiple labels. In this paper, we propose a novel approach called stable diffusion deep generative replay (SDDGR) for CIOD. Our method utilizes …

abstract application arxiv become catastrophic forgetting class cs.cv detection diffusion generative generative models improvements incremental stable diffusion type