NMS-KSD: Efficient Knowledge Distillation for Dense Object Detection via Non-Maximum Suppression and Feature Storage
Recently, many studies have proposed knowledge distillation (KD) frameworks for object detection. However, these frameworks did not take into account the inefficiencies caused by the teacher detector. The inefficiency refers to the computational cost incurred during the process of passing input data...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10988601/ |
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