# An Interactively Reinforced Paradigm for Joint Infrared-Visible Image Fusion and Saliency Object Detection

arXiv: https://arxiv.org/abs/2305.09999 · HTML: https://mlsanity.com/paper/2305.09999/

## Key facts

- Cited by 36 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 83 references that are in the map.
- First posted on arXiv 17 May 2023.

## Builds on (most cited first, 24 of 24)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [Squeeze-and-Excitation Networks](https://mlsanity.com/paper/1709.01507/) (2017)
- [Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform](https://mlsanity.com/paper/1804.02815/) (2018)
- [Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection](https://mlsanity.com/paper/2203.16220/) (2022)
- [Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement](https://mlsanity.com/paper/2012.05609/) (2020)
- [CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion](https://mlsanity.com/paper/2211.14461/) (2022)
- [DenseFuse: A Fusion Approach to Infrared and Visible Images](https://mlsanity.com/paper/1804.08361/) (2018)
- [RFN-Nest: An end-to-end residual fusion network for infrared and visible images](https://mlsanity.com/paper/2103.04286/) (2021)
- [Anomaly Detection in Autonomous Driving: A Survey](https://mlsanity.com/paper/2204.07974/) (2022)
- [Unsupervised Misaligned Infrared and Visible Image Fusion via Cross-Modality Image Generation and Registration](https://mlsanity.com/paper/2205.11876/) (2022)
- [DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion](https://mlsanity.com/paper/2003.09210/) (2020)
- [Discrete Cosine Transform Network for Guided Depth Map Super-Resolution](https://mlsanity.com/paper/2104.06977/) (2021)
- [CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion](https://mlsanity.com/paper/2211.10960/) (2022)
- [RGB-T Image Saliency Detection via Collaborative Graph Learning](https://mlsanity.com/paper/1905.06741/) (2019)
- [HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization](https://mlsanity.com/paper/2105.13084/) (2021)
- [MDLatLRR: A novel decomposition method for infrared and visible image fusion](https://mlsanity.com/paper/1811.02291/) (2018)
- [A Unified RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and A Novel Approach](https://mlsanity.com/paper/1701.02829/) (2017)
- [Multi-interactive Dual-decoder for RGB-thermal Salient Object Detection](https://mlsanity.com/paper/2005.02315/) (2020)
- [Connecting Image Denoising and High-Level Vision Tasks via Deep Learning](https://mlsanity.com/paper/1809.01826/) (2018)
- [Boosting Few-shot Fine-grained Recognition with Background Suppression and Foreground Alignment](https://mlsanity.com/paper/2210.01439/) (2022)
- [Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancement](https://mlsanity.com/paper/2112.05147/) (2021)
- [Learning with Nested Scene Modeling and Cooperative Architecture Search for Low-Light Vision](https://mlsanity.com/paper/2112.04719/) (2021)
- [PPT Fusion: Pyramid Patch Transformerfor a Case Study in Image Fusion](https://mlsanity.com/paper/2107.13967/) (2021)

## Built on by (most cited first, 30 of 36)

- [Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation](https://mlsanity.com/paper/2308.02097/) (2023)
- [CrossFuse: A Novel Cross Attention Mechanism based Infrared and Visible Image Fusion Approach](https://mlsanity.com/paper/2406.10581/) (2024)
- [Every SAM Drop Counts: Embracing Semantic Priors for Multi-Modality Image Fusion and Beyond](https://mlsanity.com/paper/2503.01210/) (2025)
- [M3Net: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition](https://mlsanity.com/paper/2308.03063/) (2023)
- [PAIF: Perception-Aware Infrared-Visible Image Fusion for Attack-Tolerant Semantic Segmentation](https://mlsanity.com/paper/2308.03979/) (2023)
- [DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-Resolution](https://mlsanity.com/paper/2503.01187/) (2025)
- [Improving Misaligned Multi-modality Image Fusion with One-stage Progressive Dense Registration](https://mlsanity.com/paper/2308.11165/) (2023)
- [TSJNet: A Multi-modality Target and Semantic Awareness Joint-driven Image Fusion Network](https://mlsanity.com/paper/2402.01212/) (2024)
- [Infrared and Visible Image Fusion with Language-Driven Loss in CLIP Embedding Space](https://mlsanity.com/paper/2402.16267/) (2024)
- [Unified-modal Salient Object Detection via Adaptive Prompt Learning](https://mlsanity.com/paper/2311.16835/) (2023)
- [Instruction-Driven Fusion of Infrared-Visible Images: Tailoring for Diverse Downstream Tasks](https://mlsanity.com/paper/2411.09387/) (2024)
- [S4Fusion: Saliency-aware Selective State Space Model for Infrared Visible Image Fusion](https://mlsanity.com/paper/2405.20881/) (2024)
- [Conti-Fuse: A Novel Continuous Decomposition-based Fusion Framework for Infrared and Visible Images](https://mlsanity.com/paper/2406.04689/) (2024)
- [DEAL: Data-Efficient Adversarial Learning for High-Quality Infrared Imaging](https://mlsanity.com/paper/2503.00905/) (2025)
- [Internal-External Boundary Attention Fusion for Glass Surface Segmentation](https://mlsanity.com/paper/2307.00212/) (2023)
- [SFDFusion: An Efficient Spatial-Frequency Domain Fusion Network for Infrared and Visible Image Fusion](https://mlsanity.com/paper/2410.22837/) (2024)
- [CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors](https://mlsanity.com/paper/2504.10888/) (2025)
- [Task-Generalized Adaptive Cross-Domain Learning for Multimodal Image Fusion](https://mlsanity.com/paper/2508.15505/) (2025)
- [Spatial-Frequency Enhanced Mamba for Multi-Modal Image Fusion](https://mlsanity.com/paper/2511.06593/) (2025)
- [Holistic Dynamic Frequency Transformer for Image Fusion and Exposure Correction](https://mlsanity.com/paper/2309.01183/) (2023)
- [SMLNet: A SPD Manifold Learning Network for Infrared and Visible Image Fusion](https://mlsanity.com/paper/2411.10679/) (2024)
- [FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolution](https://mlsanity.com/paper/2509.09427/) (2025)
- [Dual-modal Prior Semantic Guided Infrared and Visible Image Fusion for Intelligent Transportation System](https://mlsanity.com/paper/2403.16227/) (2024)
- [MMA-UNet: A Multi-Modal Asymmetric UNet Architecture for Infrared and Visible Image Fusion](https://mlsanity.com/paper/2404.17747/) (2024)
- [DePF: A Novel Fusion Approach based on Decomposition Pooling for Infrared and Visible Images](https://mlsanity.com/paper/2305.17376/) (2023)
- [Bilevel Generative Learning for Low-Light Vision](https://mlsanity.com/paper/2308.03381/) (2023)
- [HSFusion: A high-level vision task-driven infrared and visible image fusion network via semantic and geometric domain transformation](https://mlsanity.com/paper/2407.10047/) (2024)
- [textrmA^textrm2RNet: Adversarial Attack Resilient Network for Robust Infrared and Visible Image Fusion](https://mlsanity.com/paper/2412.09954/) (2024)
- [Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusion](https://mlsanity.com/paper/2604.08924/) (2026)
- [Quaternion Infrared Visible Image Fusion](https://mlsanity.com/paper/2505.02364/) (2025)

## Abstract (arXiv)

This research focuses on the discovery and localization of hidden objects in the wild and serves unmanned systems. Through empirical analysis, infrared and visible image fusion (IVIF) enables hard-to-find objects apparent, whereas multimodal salient object detection (SOD) accurately delineates the precise spatial location of objects within the picture. Their common characteristic of seeking complementary cues from different source images motivates us to explore the collaborative relationship between Fusion and Salient object detection tasks on infrared and visible images via an Interactively Reinforced multi-task paradigm for the first time, termed IRFS. To the seamless bridge of multimodal image fusion and SOD tasks, we specifically develop a Feature Screening-based Fusion subnetwork (FSFNet) to screen out interfering features from source images, thereby preserving saliency-related features. After generating the fused image through FSFNet, it is then fed into the subsequent Fusion-Guided Cross-Complementary SOD subnetwork (FC2Net) as the third modality to drive the precise prediction of the saliency map by leveraging the complementary information derived from the fused image. In addition, we develop an interactive loop learning strategy to achieve the mutual reinforcement of IVIF and SOD tasks with a shorter training period and fewer network parameters. Comprehensive experiment results demonstrate that the seamless bridge of IVIF and SOD mutually enhances their performance, and highlights their superiority.