Shibei LIU, Ying CHEN. Audio object detection network with multimodal cross level feature knowledge transfer[J]. Optics and Precision Engineering, 2024, 32(2): 237
- Optics and Precision Engineering
- Vol. 32, Issue 2, 237 (2024)
Fig. 1. Schematic of RGB， depth and audio information
Fig. 2. Multimodal knowledge distillation target detection network
Fig. 3. Cross-level fusion and no cross-level feature heatmaps
Fig. 4. Cross-level feature knowledge transfer loss based on attentional fusion
Fig. 5. Attention fusion module（AFM） and the KL divergence calculation module（KLD）
Fig. 6. Selection diagram of image and audio
Fig. 7. Example images of MAVD dataset
Fig. 8. Comparison of object detection capability under different network architecture
Fig. 9. Schematic diagram of different fusion modes
Fig. 10. Qualitative comparison of vehicle detection capability with or without LDLoss
Fig. 11. Los curves for MTALoss and MCFTLoss
Fig. 12. Qualitatively compares the vehicle detection capabilities of the baseline network and the method presented in this paper
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Table 1. Results comparison of the method and the baseline network under different faculty modes
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Table 2. This paper compares the method with classical object detection networks
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Table 3. Ablation studies for both losses
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Table 4. 损失函数中超参数和的消融研究
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Table 5. 损失函数中超参数，和的消融研究
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Table 6. Ablation studies with different fusion methods and loss calculation methods
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