Multi-task incremental learning for object detection

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How researchers see this paper

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Wanderlust: Online Continual Object Detection in the Real World (2021, methodology): “In the object detection domain, several incremental object detection algorithms [23, 27, 32, 41] adopt existing object detection datasets such as PASCAL VOC [11] and MS COCO [26] for evaluation.”
Class-Incremental Learning: A Survey (2023, background): “[266] also designs an adaptive exemplar selection strategy for efficient exemplar selection in IOD.”
Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism (2022, unknown): “Another line of researches [23, 34] on continual detection store a small number of samples(exemplars) for reviewing previous knowledge.”
Continual Detection Transformer for Incremental Object Detection (2023, methodology): “1 percentage points respectively, compared to using conventional ER [31, 43].”
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection (2023, methodology): “Implementation Details: Similar to [7,9,22,28,39,47,54, 59, 65], we use the Faster R-CNN [51] architecture with a Resnet-50 [24] backbone pretrained on ImageNet [11].”
SDDGR: Stable Diffusion-Based Deep Generative Replay for Class Incremental Object Detection (2024, background): “A photo of bird, realistic, 8K, …, details”