arXiv:2608. 05771v1 Announce Type: cross Abstract: Infrared small target detection (IRSTD) has achieved substantial progress under domain-consistent evaluation, yet detector performance often degrades markedly when generalizing to unseen infrared domains.
By Aohua Li, Jin Kuang, Yubing Lu, Pingping Liu
arXiv:2607. 17148v1 Announce Type: cross Abstract: Infrared small target detection (IRSTD) commonly relies on pixel-level mask supervision.
By Xizhe Zhang, Fan Shi, Mianzhao Wang, Jiangpeng Zheng, Xu Cheng, Shengyong Chen
arXiv:2607. 04603v1 Announce Type: cross Abstract: Infrared small target detection (IRSTD) aims to identify long distance small targets from complex infrared backgrounds, and is a fundamental task in remote sensing.
By Tianfang Zhang, Fengyi Wu, Lei Li, Chang Liu, Zhenming Peng, Huaping Zhang, Xiangyang Ji
arXiv:2606. 23825v1 Announce Type: cross Abstract: Efficient small object detection is bottlenecked by the inherent feature scarcity of tiny targets, which is further aggravated by operations of spatial-domain detectors that indiscriminately discard critical high-frequency details.
By Yuhan Rui, Shihan Qiao, Yibin Lou, Mingxi Yu, Yutong Wan, Yanqiao Chen, Dongsheng Hou, Zhen Cao, Athena Zhuoming Zhong, Qi Hao
arXiv:2606. 30215v1 Announce Type: cross Abstract: RGB-T detectors leverage the complementary strengths of visible and thermal infrared modalities, achieving robust performance under challenging conditions.
By Chao Tian, Zikun Zhou, Chao Yang, Guoqing Zhu, Zhenyu He
Visible-infrared (VIS-IR) alignment is a key pre-training task for robust multi-sensor perception. Most existing methods use uniform patch-wise contrastive learning, but this can be unreliable in VIS-IR data because imaging-physics differences make some spatially paired regions inherently less comparable, and aligning them with equal strength hinders representation learning and downstream transfer.