# TBC-Net: A real-time detector for infrared small target detection using semantic constraint

arXiv: https://arxiv.org/abs/2001.05852 · HTML: https://mlsanity.com/paper/2001.05852/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Dec 2019.

## Built on by (most cited first, 10 of 10)

- [UIU-Net: U-Net in U-Net for Infrared Small Object Detection](https://mlsanity.com/paper/2212.00968/) (2022)
- [Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines](https://mlsanity.com/paper/2406.14482/) (2024)
- [HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection](https://mlsanity.com/paper/2403.10778/) (2024)
- [ILNet: Low-level Matters for Salient Infrared Small Target Detection](https://mlsanity.com/paper/2309.13646/) (2023)
- [Infrared Small-Dim Target Detection with Transformer under Complex Backgrounds](https://mlsanity.com/paper/2109.14379/) (2021)
- [iSmallNet: Densely Nested Network with Label Decoupling for Infrared Small Target Detection](https://mlsanity.com/paper/2210.16561/) (2022)
- [CSPENet: Contour-Aware and Saliency Priors Embedding Network for Infrared Small Target Detection](https://mlsanity.com/paper/2505.09943/) (2025)
- [Revisiting the Scale Loss Function and Gaussian-Shape Convolution for Infrared Small Target Detection](https://mlsanity.com/paper/2604.09991/) (2026)
- [DuGI-MAE: Improving Infrared Mask Autoencoders via Dual-Domain Guidance](https://mlsanity.com/paper/2512.04511/) (2025)
- [SCR-Guided Difficulty-Aware Optimization for Infrared Small Target Detection](https://mlsanity.com/paper/2606.18783/) (2026)

## Abstract (arXiv)

Infrared small target detection is a key technique in infrared search and tracking (IRST) systems. Although deep learning has been widely used in the vision tasks of visible light images recently, it is rarely used in infrared small target detection due to the difficulty in learning small target features. In this paper, we propose a novel lightweight convolutional neural network TBC-Net for infrared small target detection. The TBCNet consists of a target extraction module (TEM) and a semantic constraint module (SCM), which are used to extract small targets from infrared images and to classify the extracted target images during the training, respectively. Meanwhile, we propose a joint loss function and a training method. The SCM imposes a semantic constraint on TEM by combining the high-level classification task and solve the problem of the difficulty to learn features caused by class imbalance problem. During the training, the targets are extracted from the input image and then be classified by SCM. During the inference, only the TEM is used to detect the small targets. We also propose a data synthesis method to generate training data. The experimental results show that compared with the traditional methods, TBC-Net can better reduce the false alarm caused by complicated background, the proposed network structure and joint loss have a significant improvement on small target feature learning. Besides, TBC-Net can achieve real-time detection on the NVIDIA Jetson AGX Xavier development board, which is suitable for applications such as field research with drones equipped with infrared sensors.