Infrared Traffic Object Detection Network for Edge Device Deployment

Yulan Han; Deao Chen; Tong Wu; Xianlu Liu; Chaofeng Lan

doi:10.3788/AOS241913

Acta Optica Sinica, Volume. 45, Issue 9, 0910002(2025)

Infrared Traffic Object Detection Network for Edge Device Deployment

Yulan Han^*, Deao Chen, Tong Wu, Xianlu Liu, and Chaofeng Lan

Heilongjiang Province Key Laboratory of Pattern Recognition and Information Perception, School of Measurement and Control Technology and Communication Engineering, Harbin University of Science and Technology, Harbin 150080, Heilongjiang , China

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Figures & Tables(10)

Fig. 1. Edge-DETR network model. (a) Overall framework diagram; (b) GISM; (c) zoom cat block

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Fig. 2. CAA-MELAN block

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Fig. 3. HiLo block

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Fig. 4. CFFM structure

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Fig. 5. Visualization images of infrared feature extraction by backbone network. (a) Features extracted by RT-DETR; (b) features extracted by Edge-DETR

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Fig. 6. Heatmaps of detection results. (a) Heatmaps of detection results by RT-DETR; (b) heatmaps of detection results by Edge-DETR

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Fig. 7. Comparison of detection effects on three datasets by different algorithms. (a) RGB images; (b) RGB detection images; (c) infrared images; (d) Fast R-CNN; (e) YOLOv11; (f) RT-DETR; (g) ours

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Fig. 8. Comparison of detection effects on self-built dataset by different algorithms. (a) RGB images; (b) RGB detection images; (c) infrared images; (d) Fast R-CNN; (e) YOLOv11; (f) RT-DETR; (g) ours

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Table 1. Ablation experiments on FLIR

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Table 1. Ablation experiments on FLIR

Group	CAA-MELAN	CFFM	HiLo	Shape-IoU	mAP50 /%	mAP75 /%	Params /10⁶	FLOPs /10⁹	Size /MB	FR /（frame/s）
1					49.39	29.60	19.87	56.9	38.6	51.3
2	√				51.92	30.86	12.14	38.6	23.2	43.6
3		√			50.56	30.32	19.86	59.8	39.5	41.4
4			√		50.21	30.73	19.86	56.8	26.5	57.2
5				√	50.36	30.32	19.87	56.9	38.6	51.3
6			√	√	50.23	30.74	19.87	48.9	30.6	41.9
7	√	√			52.67	31.47	10.69	34.7	21.0	36.7
8	√	√	√	√	53.89	32.34	10.69	34.7	21.0	36.7

Table 2. Comparative experiment results on different datasets

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Table 2. Comparative experiment results on different datasets

Model	LLVIP		FLIR		KAIST		Self-built dataset		FLOPs /10⁹	Params /10⁶	Size /MB
Model	mAP50 /%	mAP75 /%	mAP50 /%	mAP75 /%	mAP50 /%	mAP75 /%	mAP50 /%	mAP75 /%	FLOPs /10⁹	Params /10⁶	Size /MB
SSD^［5］	91.12	56.27	20.03	7.54	41.49	18.14	81.68	62.51	62.7	26.20	100
Fast R-CNN^［6］	96.14	68.16	23.42	8.41	41.51	11.85	83.81	67.60	177.5	41.30	129
YOLOv5m^［8］	94.61	72.21	44.20	27.50	47.56	34.51	82.22	65.94	114.5	46.60	81
YOLOv8m^［9］	96.22	76.55	48.10	30.71	47.13	35.55	83.54	66.88	78.7	25.80	92
YOLOv10m^［10］	96.55	78.23	50.37	31.09	47.83	35.86	83.84	63.39	59.1	15.80	63
YOLOv11m^［11］	96.49	78.92	51.32	31.26	47.72	36.14	83.96	64.79	67.9	20.10	38
DETR-R50^［13］	95.43	76.33	46.76	29.24	44.31	36.43	82.11	63.30	86.6	41.70	171
Deformable DETR^［14］	96.48	78.54	49.33	30.47	46.96	34.41	83.03	65.37	42.2	27.10	183
RT-DETR^［15］	96.57	79.85	49.39	29.60	48.14	36.27	83.19	66.31	56.9	19.87	38
Edge-DETR（ours）	97.98	82.55	53.89	32.34	48.28	36.55	84.30	68.42	34.7	10.69	21

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Yulan Han, Deao Chen, Tong Wu, Xianlu Liu, Chaofeng Lan. Infrared Traffic Object Detection Network for Edge Device Deployment[J]. Acta Optica Sinica, 2025, 45(9): 0910002

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Paper Information

Category: Image Processing

Received: Dec. 19, 2024

Accepted: Mar. 11, 2025

Published Online: May. 20, 2025

The Author Email: Yulan Han (hanyulan@hrbust.edu.cn)

DOI:10.3788/AOS241913

CSTR:32393.14.AOS241913

Topics

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