Tianlei MA, Xinhao LIU, Jinzhu PENG, Zhiqiang KAI, Hao WANG. Adaptive tracking method for infrared small targets in dynamic and complex scenes (invited)[J]. Infrared and Laser Engineering, 2025, 54(3): 20240496

Search by keywords or author
- Infrared and Laser Engineering
- Vol. 54, Issue 3, 20240496 (2025)

Fig. 1. Tracking framework of the proposed network (DTFE module represent dynamic template feature enhancement module; MSA module represent multi-layer self-attention module; ATU module represent adaptive template update module)

Fig. 2. Dynamic Template Feature Enhancement (DTFE) module

Fig. 3. Multi-layer Self-attention (MSA) module (This module consists of encoder-decoder self-attention module and pixel-level self-attention module connected in series)

Fig. 4. Visualization of template features

Fig. 5. Success rate curves of different algorithms on Seq1-Seq8

Fig. 6. Precision curves of different algorithms on Seq1-Seq8

Fig. 7. Visualization results of different algorithms on Seq1-Seq8

Fig. 8. Feature visualization under scale changes (The scale gradually decreases from left to right)

Fig. 9. Feature visualization under posture changes

Fig. 10. The visualization results of the proposed method in scenarios with scale and attitude changes (Scale change in the first row, posture change in the second row)
|
Table 1. The structure of multi-scale feature extraction and fusion network
|
Table 2. Quantitative comparison results (success rate)
|
Table 3. Quantitative comparison results (precision)
|
Table 4. The success rate (IOU ≥0.5) and precision (P ≤ 5 pixel) of different backbone networks
|
Table 5. The effectiveness of each proposed module in improving tracking performance
|
Table 6. Quantitative analysis of performance indicators under scale and attitude changes

Set citation alerts for the article
Please enter your email address