CL-CLIP uses CLIP image-text cost volumes to create class-specific pathways processed by a multi-expert RoI head, improving continual object detection on VOC and COCO over the F-ViT baseline.
idpa: Instance decoupled prompt attention for incremental medical object detection.arXiv preprint arXiv:2506.00406,
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Integrates SAM-Audio dense representations with guided attention and dual distillation for audio-visual class-incremental learning, reporting consistent outperformance on benchmarks.
citing papers explorer
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CL-CLIP: CLIP-Based Continual Learning Framework with Cost-Volume Category Decoupling for Object Detection
CL-CLIP uses CLIP image-text cost volumes to create class-specific pathways processed by a multi-expert RoI head, improving continual object detection on VOC and COCO over the F-ViT baseline.
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Listen, Look, and Learn: Learning Without Forgetting through SAM-Audio
Integrates SAM-Audio dense representations with guided attention and dual distillation for audio-visual class-incremental learning, reporting consistent outperformance on benchmarks.