TY - GEN
T1 - Asymmetric contextual modulation for infrared small target detection
AU - Dai, Yimian
AU - Wu, Yiquan
AU - Zhou, Fei
AU - Barnard, Kobus
N1 - Funding Information:
Supported by NSFC No. 61573183, Open Project of NLPR No. 201900029, NUAA PhD visiting scholar project No. 180104DF03, and CSC No. 201806830039.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/1
Y1 - 2021/1
N2 - Single-frame infrared small target detection remains a challenge not only due to the scarcity of intrinsic target characteristics but also because of lacking a public dataset. In this paper, we first contribute an open dataset with high-quality annotations to advance the research in this field. We also propose an asymmetric contextual modulation module specially designed for detecting infrared small targets. To better highlight small targets, besides a top-down global contextual feedback, we supplement a bottom-up modulation pathway based on point-wise channel attention for exchanging high-level semantics and subtle low-level details. We report ablation studies and comparisons to state-of-the-art methods, where we find that our approach performs significantly better. Our dataset and code are available online 1.
AB - Single-frame infrared small target detection remains a challenge not only due to the scarcity of intrinsic target characteristics but also because of lacking a public dataset. In this paper, we first contribute an open dataset with high-quality annotations to advance the research in this field. We also propose an asymmetric contextual modulation module specially designed for detecting infrared small targets. To better highlight small targets, besides a top-down global contextual feedback, we supplement a bottom-up modulation pathway based on point-wise channel attention for exchanging high-level semantics and subtle low-level details. We report ablation studies and comparisons to state-of-the-art methods, where we find that our approach performs significantly better. Our dataset and code are available online 1.
UR - http://www.scopus.com/inward/record.url?scp=85100792071&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100792071&partnerID=8YFLogxK
U2 - 10.1109/WACV48630.2021.00099
DO - 10.1109/WACV48630.2021.00099
M3 - Conference contribution
AN - SCOPUS:85100792071
T3 - Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021
SP - 949
EP - 958
BT - Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021
Y2 - 5 January 2021 through 9 January 2021
ER -