# Attentional Local Contrast Networks for Infrared Small Target Detection

arXiv: https://arxiv.org/abs/2012.08573 · HTML: https://mlsanity.com/paper/2012.08573/

## Key facts

- Cited by 109 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Dec 2020.

## Built on by (most cited first, 30 of 109)

- [Dense Nested Attention Network for Infrared Small Target Detection](https://mlsanity.com/paper/2106.00487/) (2021)
- [UIU-Net: U-Net in U-Net for Infrared Small Object Detection](https://mlsanity.com/paper/2212.00968/) (2022)
- [SCTransNet: Spatial-channel Cross Transformer Network for Infrared Small Target Detection](https://mlsanity.com/paper/2401.15583/) (2024)
- [MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection](https://mlsanity.com/paper/2403.02148/) (2024)
- [Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection with Single Point Supervision](https://mlsanity.com/paper/2304.01484/) (2023)
- [MTU-Net: Multi-level TransUNet for Space-based Infrared Tiny Ship Detection](https://mlsanity.com/paper/2209.13756/) (2022)
- [IRSAM: Advancing Segment Anything Model for Infrared Small Target Detection](https://mlsanity.com/paper/2407.07520/) (2024)
- [Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines](https://mlsanity.com/paper/2406.14482/) (2024)
- [One-Stage Cascade Refinement Networks for Infrared Small Target Detection](https://mlsanity.com/paper/2212.08472/) (2022)
- [SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detection](https://mlsanity.com/paper/2412.20665/) (2024)
- [Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection](https://mlsanity.com/paper/2304.04442/) (2023)
- [ILNet: Low-level Matters for Salient Infrared Small Target Detection](https://mlsanity.com/paper/2309.13646/) (2023)
- [SIRST-5K: Exploring Massive Negatives Synthesis with Self-supervised Learning for Robust Infrared Small Target Detection](https://mlsanity.com/paper/2403.05416/) (2024)
- [Pick of the Bunch: Detecting Infrared Small Targets Beyond Hit-Miss Trade-Offs via Selective Rank-Aware Attention](https://mlsanity.com/paper/2408.03717/) (2024)
- [Thermal3D-GS: Physics-induced 3D Gaussians for Thermal Infrared Novel-view Synthesis](https://mlsanity.com/paper/2409.08042/) (2024)
- [EFLNet: Enhancing Feature Learning for Infrared Small Target Detection](https://mlsanity.com/paper/2307.14723/) (2023)
- [Triple-domain Feature Learning with Frequency-aware Memory Enhancement for Moving Infrared Small Target Detection](https://mlsanity.com/paper/2406.06949/) (2024)
- [Infrared Small-Dim Target Detection with Transformer under Complex Backgrounds](https://mlsanity.com/paper/2109.14379/) (2021)
- [Multi-Scale Direction-Aware Network for Infrared Small Target Detection](https://mlsanity.com/paper/2406.02037/) (2024)
- [DATransNet: Dynamic Attention Transformer Network for Infrared Small Target Detection](https://mlsanity.com/paper/2409.19599/) (2024)
- [RPCANet++: Deep Interpretable Robust PCA for Sparse Object Segmentation](https://mlsanity.com/paper/2508.04190/) (2025)
- [Probing Deep into Temporal Profile Makes the Infrared Small Target Detector Much Better](https://mlsanity.com/paper/2506.12766/) (2025)
- [DRPCA-Net: Make Robust PCA Great Again for Infrared Small Target Detection](https://mlsanity.com/paper/2507.09541/) (2025)
- [Background Semantics Matter: Cross-Task Feature Exchange Network for Clustered Infrared Small Target Detection](https://mlsanity.com/paper/2407.20078/) (2024)
- [Infrared Small Target Detection in Satellite Videos: A New Dataset and A Novel Recurrent Feature Refinement Framework](https://mlsanity.com/paper/2409.12448/) (2024)
- [Local Motion and Contrast Priors Driven Deep Network for Infrared Small Target Super-Resolution](https://mlsanity.com/paper/2201.01014/) (2022)
- [Diff-Mosaic: Augmenting Realistic Representations in Infrared Small Target Detection via Diffusion Prior](https://mlsanity.com/paper/2406.00632/) (2024)
- [Towards Robust Infrared Small Target Detection: A Feature-Enhanced and Sensitivity-Tunable Framework](https://mlsanity.com/paper/2407.20090/) (2024)
- [Beyond Full Labels: Energy-Double-Guided Single-Point Prompt for Infrared Small Target Label Generation](https://mlsanity.com/paper/2408.08191/) (2024)
- [SMPISD-MTPNet: Scene Semantic Prior-Assisted Infrared Ship Detection Using Multi-Task Perception Networks](https://mlsanity.com/paper/2407.18487/) (2024)

## Abstract (arXiv)

To mitigate the issue of minimal intrinsic features for pure data-driven methods, in this paper, we propose a novel model-driven deep network for infrared small target detection, which combines discriminative networks and conventional model-driven methods to make use of both labeled data and the domain knowledge. By designing a feature map cyclic shift scheme, we modularize a conventional local contrast measure method as a depth-wise parameterless nonlinear feature refinement layer in an end-to-end network, which encodes relatively long-range contextual interactions with clear physical interpretability. To highlight and preserve the small target features, we also exploit a bottom-up attentional modulation integrating the smaller scale subtle details of low-level features into high-level features of deeper layers. We conduct detailed ablation studies with varying network depths to empirically verify the effectiveness and efficiency of the design of each component in our network architecture. We also compare the performance of our network against other model-driven methods and deep networks on the open SIRST dataset as well. The results suggest that our network yields a performance boost over its competitors. Our code, trained models, and results are available online.