← Back to all news
arXiv AI By Tongtong Wang, Mingzhu Xu, Chenglong Yu, Jing Wang, Xiaohui Lin, Weili Guan

ADGNet: Asymmetric Dual-text Guided Network for Infrared Small Target Detection

Read the original on arXiv AI →

ADGNet introduces an Asymmetric Dual-text Guided Network for infrared small target detection, addressing challenges of pixel-level methods and multimodal approaches that lack regional guidance. It employs an Asymmetric Dual-text Prompt (ADP) with an abstract target prompt and a detailed background prompt, and an Asymmetric Dual-Branch Interaction (ADBI) module to guide visual features separately, followed by an Adaptive Feature Aggregation (AFA) module for dynamic fusion. The authors also create an Asymmetric Image-Text Infrared (AITIR) dataset with asymmetric text annotations for three public datasets, and show that ADGNet outperforms 21 state‑of‑the‑art methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

Related stories

arXiv Computer Vision
Aug 28

DOD-SA: Infrared-Visible Decoupled Object Detection with Single-Modality Annotations

The paper introduces DOD-SA, a framework for infrared-visible object detection that uses only single-modality annotations. It employs a Collaborative Teacher-Student Network with a single-modality branch and a dual-modality decoupled branch to transfer knowledge across modalities, and a Progressive and Self‑Tuning Training Strategy to refine pseudo‑labels. A Pseudo Label Assigner is also designed to align labels between modalities during training.

By Hang Jin, Chenqiang Gao, Junjie Guo, Fangcen Liu, Qinyao Chang, Kanghui Tian, Deyu Meng
computer-vision
More like this →
Hugging Face Trending Papers
Jul 2

Boosting Infrared Small Target Detection via Logit-Domain Contrast and Adaptive Shape Refinement

Infrared small target detection (IRSTD) remains challenging due to tiny target size, low signal-to-noise ratio, severe foreground-background imbalance, and blurred boundaries in complex scenes. Existing methods usually rely on post-activation probability-domain supervision for discrimination, where weak targets and strong clutter may produce saturated and close probabilities, limiting weak-target discrimination.

diffusion
More like this →
Hugging Face Trending Papers
Jul 26

ConFusion: Continuous Fusion Space Learning for Fine-Grained Controllable Infrared and Visible Image Fusion

Controllable infrared-visible image fusion aims to integrate complementary thermal and structural information with flexible region-aware modulation, producing fused images that adapt to diverse user requirements and downstream tasks. However, existing methods typically rely on predefined discrete control conditions, leading to a sparse space that fails to support fine-grained modulation demands.

llmsmultimodalbenchmarkssafety
More like this →