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20202026
most citedMapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection with Single Point Supervision

131 citations · 180 across the 7 of their papers we have counts for

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9 papers · 1 filter

cs.CV2026★ 10 cited

Dynamic High-frequency Convolution for Infrared Small Target Detection

Ruojing Li, Chao Xiao, Qian Yin +5

Infrared small targets are typically tiny and locally salient, which belong to high-frequency components (HFCs) in images. Single-frame infrared small target (SIRST) detection is c…

cs.CV2025

Probing Deep into Temporal Profile Makes the Infrared Small Target Detector Much Better

Ruojing Li, Wei An, Yingqian Wang +6

Infrared small target (IRST) detection is challenging in simultaneously achieving precise, robust, and efficient performance due to extremely dim targets and strong interference. C…

cs.CV2024★ 34 cited

Infrared Small Target Detection in Satellite Videos: A New Dataset and A Novel Recurrent Feature Refinement Framework

Xinyi Ying, Li Liu, Zaipin Lin +7

Multi-frame infrared small target (MIRST) detection in satellite videos is a long-standing, fundamental yet challenging task for decades, and the challenges can be summarized as: F…

cs.CV2024

The First Competition on Resource-Limited Infrared Small Target Detection Challenge: Methods and Results

Boyang Li, Xinyi Ying, Ruojing Li +3

In this paper, we briefly summarize the first competition on resource-limited infrared small target detection (namely, LimitIRSTD). This competition has two tracks, including weakl…

cs.CV2024

Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines

Xinyi Ying, Chao Xiao, Ruojing Li +13

Small object detection (SOD) has been a longstanding yet challenging task for decades, with numerous datasets and algorithms being developed. However, they mainly focus on either v…

cs.CV2024★ 2 cited

Multi-Scale Direction-Aware Network for Infrared Small Target Detection

Jinmiao Zhao, Zelin Shi, Chuang Yu +3

Infrared small target detection faces the problem that it is difficult to effectively separate the background and the target. Existing deep learning-based methods focus on edge and…