# HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection

arXiv: https://arxiv.org/abs/2403.10778 · HTML: https://mlsanity.com/paper/2403.10778/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 27 references that are in the map.
- First posted on arXiv 16 Mar 2024.

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [CBAM: Convolutional Block Attention Module](https://mlsanity.com/paper/1807.06521/) (2018)
- [ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks](https://mlsanity.com/paper/1910.03151/) (2019)
- [Asymmetric Contextual Modulation for Infrared Small Target Detection](https://mlsanity.com/paper/2009.14530/) (2020)
- [UIU-Net: U-Net in U-Net for Infrared Small Object Detection](https://mlsanity.com/paper/2212.00968/) (2022)
- [Reweighted Infrared Patch-Tensor Model With Both Non-Local and Local Priors for Single-Frame Small Target Detection](https://mlsanity.com/paper/1703.09157/) (2017)
- [Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic Segmentation](https://mlsanity.com/paper/2302.13765/) (2023)
- [AGPCNet: Attention-Guided Pyramid Context Networks for Infrared Small Target Detection](https://mlsanity.com/paper/2111.03580/) (2021)
- [TBC-Net: A real-time detector for infrared small target detection using semantic constraint](https://mlsanity.com/paper/2001.05852/) (2019)
- [MTLDesc: Looking Wider to Describe Better](https://mlsanity.com/paper/2203.07003/) (2022)

## Built on by (most cited first, 18 of 18)

- [Generalization Boosted Adapter for Open-Vocabulary Segmentation](https://mlsanity.com/paper/2409.08468/) (2024)
- [Seeing Through the Noise: Improving Infrared Small Target Detection and Segmentation from Noise Suppression Perspective](https://mlsanity.com/paper/2508.06878/) (2025)
- [Lost in UNet: Improving Infrared Small Target Detection by Underappreciated Local Features](https://mlsanity.com/paper/2406.13445/) (2024)
- [Dual-Task Learning for Dead Tree Detection and Segmentation with Hybrid Self-Attention U-Nets in Aerial Imagery](https://mlsanity.com/paper/2503.21438/) (2025)
- [PSTNet: Enhanced Polyp Segmentation with Multi-scale Alignment and Frequency Domain Integration](https://mlsanity.com/paper/2409.08501/) (2024)
- [CSPENet: Contour-Aware and Saliency Priors Embedding Network for Infrared Small Target Detection](https://mlsanity.com/paper/2505.09943/) (2025)
- [TY-RIST: Tactical YOLO Tricks for Real-time Infrared Small Target Detection](https://mlsanity.com/paper/2509.22909/) (2025)
- [MASF-YOLO: An Improved YOLOv11 Network for Small Object Detection on Drone View](https://mlsanity.com/paper/2504.18136/) (2025)
- [Ivan-ISTD: Rethinking Cross-domain Heteroscedastic Noise Perturbations in Infrared Small Target Detection](https://mlsanity.com/paper/2510.12241/) (2025)
- [WS-DETR: Robust Water Surface Object Detection through Vision-Radar Fusion with Detection Transformer](https://mlsanity.com/paper/2504.07441/) (2025)
- [Optimization of Module Transferability in Single Image Super-Resolution: Universality Assessment and Cycle Residual Blocks](https://mlsanity.com/paper/2505.03522/) (2025)
- [Space Object Detection using Multi-frame Temporal Trajectory Completion Method](https://mlsanity.com/paper/2510.19220/) (2025)
- [DCCS-Det: Directional Context and Cross-Scale-Aware Detector for Infrared Small Target](https://mlsanity.com/paper/2601.16428/) (2026)
- [MDAFNet: Multiscale Differential Edge and Adaptive Frequency Guided Network for Infrared Small Target Detection](https://mlsanity.com/paper/2601.16434/) (2026)
- [RSTNet: Enhancing Small-Target Recognition in Noisy SAR Imagery via Robust Feature Learning and Distribution-Aware Regression](https://mlsanity.com/paper/2602.23820/) (2026)
- [Rethinking Representations for Cross-Domain Infrared Small Target Detection: A Generalizable Perspective from the Frequency Domain](https://mlsanity.com/paper/2604.01934/) (2026)
- [Temporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection](https://mlsanity.com/paper/2606.27655/) (2026)
- [Initialization and Stopping Tolerance in CPU Dermoscopic Segmentation](https://mlsanity.com/paper/2609.25685/) (2026)

## Abstract (arXiv)

Infrared small object detection is an important computer vision task involving the recognition and localization of tiny objects in infrared images, which usually contain only a few pixels. However, it encounters difficulties due to the diminutive size of the objects and the generally complex backgrounds in infrared images. In this paper, we propose a deep learning method, HCF-Net, that significantly improves infrared small object detection performance through multiple practical modules. Specifically, it includes the parallelized patch-aware attention (PPA) module, dimension-aware selective integration (DASI) module, and multi-dilated channel refiner (MDCR) module. The PPA module uses a multi-branch feature extraction strategy to capture feature information at different scales and levels. The DASI module enables adaptive channel selection and fusion. The MDCR module captures spatial features of different receptive field ranges through multiple depth-separable convolutional layers. Extensive experimental results on the SIRST infrared single-frame image dataset show that the proposed HCF-Net performs well, surpassing other traditional and deep learning models. Code is available at https://github.com/zhengshuchen/HCFNet.