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https://github.com/zyrant/Summary-of-RGB-T-Salient-Object-Detection-and-Semantic-segmentation

Summary of RGB-T Salient Object Detection, Semantic segmentation and Crowd Counting.
https://github.com/zyrant/Summary-of-RGB-T-Salient-Object-Detection-and-Semantic-segmentation
crowd-counting rgbt salient-object-detection semantic-segmentation
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Summary of RGB-T Salient Object Detection, Semantic segmentation and Crowd Counting.
Host: GitHub
URL: https://github.com/zyrant/Summary-of-RGB-T-Salient-Object-Detection-and-Semantic-segmentation
Owner: zyrant
Created: 2021-11-12T08:51:50.000Z (over 2 years ago)
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Last Pushed: 2024-01-07T08:53:06.000Z (6 months ago)
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Topics: crowd-counting, rgbt, salient-object-detection, semantic-segmentation
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awesome-salient-object-detection - RGB-T Salient Object Detection and Semantic segmentation
README

        # Summary of RGB-T Salient Object Detection, Semantic segmentation and Crowd Counting

![-RGBT-red](https://user-images.githubusercontent.com/38373305/205479612-e61d11b4-6c3e-4eb0-8d19-2e7170eb7783.svg)

![-Salient Object detection-green](https://user-images.githubusercontent.com/38373305/205479614-82129ebb-e5cd-4de5-9b3e-9ad046591fba.svg)

![- Semantic segmentation-blue](https://user-images.githubusercontent.com/38373305/205479615-5113eb42-d5e1-4428-aeb4-628be67964ce.svg)

![-Crowd Counting-yellow](https://user-images.githubusercontent.com/38373305/205479622-8112267b-48a3-477c-ae09-7d624e8b3308.svg)

Provide a summary of RGB-T-Salient-Object-Detection, Semantic segmentation and Crowd Counting 
 

(**Paper, Code, Dataset, Evaluation and more**). 

--------------------------------------------------------------------------------------

:running: **keep updating.** :running:  

🚩**2023.12.21 Add some papers.** 


🚩**2023.9.28 RGBT SOD: Add one paper, RGBT SS: Add three papers.** 


🚩**2023.7.7 Add some representative papers from the first half of 2023.** 


🚩**2023.5.8 RGBT SOD/SS/CC: Add one RAL paper.** 


--------------------------------------------------------------------------------------

## Content:

1.  RGB-T Salient Object Detection 

2.  RGB-T Semantic segmentation 

3.  RGB-T Crowd Counting 

4.   Dataset 

5.  Evaluation 

6.  Other Summary 

7.  Acknowledgement 

--------------------------------------------------------------------------------------

# RGB-T Salient Object Detection     

## 2017       

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **ISCID** | Learning Multiscale Deep Features and SVM Regressors for Adaptive RGB-T Saliency Detection | [Paper](https://ieeexplore.ieee.org/document/8275796)/Code

## 2018       

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **IGTA** | RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and a Novel Approach | [Paper](https://link.springer.com/chapter/10.1007/978-981-13-1702-6_36)/[Code](https://github.com/lz118/RGBT-Salient-Object-Detection)

## 2019       

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **MIPR** | M3S-NIR: Multi-Modal Multi-Scale Noise-Insensitive Ranking for RGB-T Saliency Detection | [Paper](https://ieeexplore.ieee.org/document/8695412)/[Code](https://github.com/lz118/RGBT-Salient-Object-Detection)

02 | **TMM** | RGB-T Image Saliency Detection via Collaborative Graph Learning | [Paper](https://ieeexplore.ieee.org/document/8744296)/[Code](https://github.com/lz118/RGBT-Salient-Object-Detection)

03 | **TCSVT** | RGBT Salient Object Detection: Benchmark and A Novel Cooperative Ranking Approach | [Paper](https://ieeexplore.ieee.org/document/8891733)/[Code](https://github.com/lz118/RGBT-Salient-Object-Detection)

## 2020       

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **TIP** | RGB-T Salient Object Detection via Fusing Multi-Level CNN Features | [Paper](https://ieeexplore.ieee.org/document/8935533)/Code

02 | **TCSVT** | Revisiting Feature Fusion for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/document/9161021)/Code

## 2021      

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **TCSVT** | ECFFNet: Effective and Consistent Feature Fusion Network for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/document/9420662)/[Results(pin:tx48)](https://pan.baidu.com/share/init?surl=Cp6RQMwX3GOTdn3PNyQ72A)

02 | **TCSVT** | Unified Information Fusion Network for Multi-Modal RGB-D and RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/document/9439490)/Code

03 | **TCSVT** | CGFNet: Cross-Guided Fusion Network for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/document/9493207)/[Code](https://github.com/wangjie0825/CGFNet)

04 | **TCSVT** | Efficient Context-Guided Stacked Refinement Network for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/document/9505635)/[Code](https://github.com/huofushuo/CSRNet)

05 | **SPL** | TSFNet: Two-Stage Fusion Network for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/document/9508840)/Code

06 | **TETCI** | APNet: Adversarial Learning Assistance and Perceived Importance Fusion Network for All-Day RGB-T Salient Object Detection| [Paper](https://ieeexplore.ieee.org/document/9583676)/[Code](https://github.com/zyrant/APNet)

07 | **TIP** | Multi-Interactive Dual-Decoder for RGB-Thermal Salient Object Detection| [Paper](https://ieeexplore.ieee.org/document/9454273)/[Code](https://github.com/lz118/Multi-interactive-Dual-decoder)

08 | **TCSVT** | SwinNet: Swin Transformer drives edge-aware RGB-D and RGB-T salient object detection| [Paper](https://ieeexplore.ieee.org/document/9611276)/[Code](https://github.com/liuzywen/SwinNet)

09 | **TCSVT** | Multi-graph Fusion and Learning for RGBT Image Saliency Detection| [Paper](https://ieeexplore.ieee.org/document/9389777)/Code

10 | **CYBER** | Salient Target Detection in RGB-T Image based on Multi-level Semantic Information| [Paper](https://ieeexplore.ieee.org/document/9588280)/Code

## 2022    

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **Applied Intelligence** | RGB-T salient object detection via CNN feature and result saliency map fusion | [Paper](https://link.springer.com/article/10.1007/s10489-021-02984-1)/Code

02 | **Neurocomputing** | Multi-modal Interactive Attention and Dual Progressive Decoding Network for RGB-D/T Salient Object Detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0925231222002971)/[Code](https://github.com/Liangyh18/MIA_DPD)

03 | **TCSVT** | CGMDRNet: Cross-Guided Modality Difference Reduction Network for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/9756028)/Code

04 | **arxiv** | Glass Segmentation with RGB-Thermal Image Pairs | [Paper](https://arxiv.org/abs/2204.05453)/[Code](https://github.com/Dong-Huo/RGB-T-Glass-Segmentation)

05 | **TIP** | Weakly Alignment-free RGBT Salient Object Detection with Deep Correlation Network | [Paper](https://ieeexplore.ieee.org/abstract/document/9779787)/[Code](https://github.com/lz118/Deep-Correlation-Network)

06 | **TIM** | Real-time One-stream Semantic-guided Refinement Network for RGB-Thermal Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/9803225)/[Code](https://github.com/huofushuo/OSRNet)

07 | **TCSVT** | Cross-Collaborative Fusion-Encoder Network for Robust RGB-Thermal Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/9801871)/[Code](https://git.openi.org.cn/OpenVision/CCFENet)

08 | **EAAI** | Unidirectional RGB-T salient object detection with intertwined driving of encoding and fusion | [Paper](https://www.sciencedirect.com/science/article/pii/S0952197622002743?casa_token=U7ht7JQv8I0AAAAA:qDCBrnwUB5vZGaE4veYfJnqwnvOfQiShCo_h5R13B_eEoqMdp0zj2Uec4lTusZjLS1rPxemxoiY)/Code

09 | **MVA** | EAF-Net: an enhancement and aggregation–feedback network for RGB-T salient object detection | [Paper](https://link.springer.com/article/10.1007/s00138-022-01312-y)/Code

11 | **arxiv** | Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection | [Paper](https://arxiv.org/abs/2207.03558)/[Code](https://github.com/jxr326/SwinMCNet)

12 | **CVIU** | Enabling modality interactions for RGB-T salient object detection | [Paper](https://www.sciencedirect.com/science/article/pii/S1077314222001047?casa_token=C76YSYF1K0sAAAAA:sdxNjSIR7xXcAt36D301rTrGYoqaKkMG42z2Uz7la0F675vHQo_BSQB94mZfXI_LsmX6fmvFaw)/Code

13 | **Applied Intelligence** | Modal complementary fusion network for RGB-T salient object detection | [Paper](https://link.springer.com/article/10.1007/s10489-022-03950-1)/[Code](https://github.com/dotaball/MCFNet)

14 | **TMM** | Does Thermal really always matter for RGB-T salient object detection | [Paper](https://arxiv.org/pdf/2210.04266.pdf)/[Code](https://rmcong.github.io/proj_TNet.html)

15 | **Arxiv** | Interactive Context-Aware Network for RGB-T Salient Object Detection | [Paper](https://arxiv.org/pdf/2211.06097.pdf)/Code

16 | **DSP** | MFENet: Multitype fusion and enhancement network for detecting salient objects in RGB-T images | [Paper](https://www.sciencedirect.com/science/article/pii/S1051200422004444)/[Code](https://github.com/wujunyi1412/MFENet_DSP)

17 | **PR** | Cross-modal co-feedback cellular automata for RGB-T saliency detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0031320322006185)/Code

18 | **KBS** | Asymmetric cross-modal activation network for RGB-T salient object detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0950705122011406)/[Code](https://github.com/xanxuso/ACMANet)

## 2023    

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **TCSVT** | Cross-Modality Double Bidirectional Interaction and Fusion Network for RGB-T Salient Object Detection  | [Paper](https://ieeexplore.ieee.org/abstract/document/10032588)/Code

02 | **TIP** | LSNet: Lightweight Spatial Boosting Network for Detecting Salient Objects in RGB-Thermal Images | [Paper](https://ieeexplore.ieee.org/document/10042233)/[Code](https://github.com/zyrant/LSNet)

03 | **ICME** | Scribble-Supervised RGB-T Salient Object Detection | [Paper](https://arxiv.org/abs/2303.09733)/[Code](https://github.com/liuzywen/RGBTScribble-ICME2023)

04 | **RAL** | Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks | [Paper](https://ieeexplore.ieee.org/document/10113725)/[Code](https://github.com/freeformrobotics/eaefnet)

05 | **EAAI** | Thermal images-aware guided early fusion network for cross-illumination RGB-T salient object detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0952197622006303)/[Code](https://github.com/VDT-2048/TAGFNet)

06 | **TMM** | MFFNet: Multi-modal Feature Fusion Network for V-D-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/10171982)/Code

07 | **Neurocomputing** | Feature aggregation with transformer for RGB-T salient object detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0925231223004526)/[Code](https://github.com/ELOESZHANG/FANet)

08 | **Neurocomputing** | MENet: Lightweight multimodality enhancement network for detecting salient objects in RGB-thermal images | [Paper](https://www.sciencedirect.com/science/article/pii/S0925231223000358)/Code

09 | **KBS** | Three-stream interaction decoder network for RGB-thermal salient object detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0950705122011005)/[Code](https://github.com/huofushuo/TIDNet)

11 | **TIP** | Position-Aware Relation Learning for RGB-Thermal Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/10113883)/Code

11 | **TCSVT** | Multiple Graph Affinity Interactive Network and a Variable Illumination Dataset for RGBT Image Salient Object Detection | [Paper](https://ieeexplore.ieee.org/document/10003255)/[Code](https://github.com/huanglm-me/VI-RGBT1500)

12 | **TIP** | CAVER: Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/10015667)/[Code](https://github.com/lartpang/caver)

13 | **PR** | Cross-modal co-feedback cellular automata for RGB-T saliency detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0031320322006185)/Code

14 | **TIP** | WaveNet: Wavelet Network With Knowledge Distillation for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/10127616)/[Code](https://github.com/nowander/WaveNe)

15 | **ICIP** | Feature Enhancement and Fusion for RGB-T Salient Object Detection | [Paper](https://ieeexplore.ieee.org/abstract/document/10222404)/Code

16 | **arxiv** | All in One: RGB, RGB-D, and RGB-T Salient Object Detection | [Paper](https://arxiv.org/abs/2311.14746)/Code

17 | **ACM MM** | Saliency Prototype for RGB-D and RGB-T Salient Object Detection | [Paper](https://dl.acm.org/doi/abs/10.1145/3581783.3612466)/[Code](https://github.com/ZZ2490/SPNet)

18 | **PR** | Frequency-aware feature aggregation network with dual-task consistency for RGB-T salient object detection | [Paper](https://www.sciencedirect.com/science/article/pii/S0031320323007409)/Code

18 | **arxiv** | Unified-modal Salient Object Detection via Adaptive Prompt Learning | [Paper](https://arxiv.org/abs/2311.16835)/Code

--------------------------------------------------------------------------------------

# RGB-T Semantic segmentation     

## 2017       

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **IROS** | MFNet: Towards Real-Time Semantic Segmentation for Autonomous Vehicles with Multi-Spectral Scenes | [Paper](https://ieeexplore.ieee.org/document/8206396)/[Code](https://github.com/haqishen/MFNet-pytorch)

## 2019       

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **RAL** | RTFNet: RGB-Thermal Fusion Network for Semantic Segmentation of Urban Scenes | [Paper](https://ieeexplore.ieee.org/document/8666745)/[Code](https://github.com/yuxiangsun/RTFNet)

## 2020      

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **ICRA** | PST900: RGB-Thermal Calibration, Dataset and Segmentation Network | [Paper](https://ieeexplore.ieee.org/document/9196831)/[Code](https://github.com/ShreyasSkandanS/pst900_thermal_rgb)

02 | **TASE** | FuseSeg: Semantic Segmentation of Urban Scenes Based on RGB and Thermal Data Fusion | [Paper](https://ieeexplore.ieee.org/document/9108585)/Code

02 | **CINE** | Using thermal intensities to build conditional random fields for object segmentation at night | [Paper](https://ieeexplore.ieee.org/document/9080716)/Code

## 2021     

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

:triangular_flag_on_post:01 | **TIP** | GMNet: Graded-Feature Multilabel-Learning Network for RGB-Thermal Urban Scene Semantic Segmentation | [Paper](https://ieeexplore.ieee.org/document/9531449)/[Code](https://github.com/Jinfu0913/GMNet)

:triangular_flag_on_post:02 | **CVPR** | ABMDRNet: Adaptive-weighted Bi-directional Modality Difference Reduction Network for RGB-T Semantic Segmentation | [Paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_ABMDRNet_Adaptive-Weighted_Bi-Directional_Modality_Difference_Reduction_Network_for_RGB-T_Semantic_CVPR_2021_paper.pdf)/Code

03 | **IROS** | FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation | [Paper](https://arxiv.org/pdf/2110.08988.pdf)/[Code](https://github.com/matrixgame2018/FEANet)

04 | **Measurement** | Robust semantic segmentation based on RGB-thermal in variable lighting scenes | [Paper](https://www.sciencedirect.com/science/article/pii/S0263224121010903)/Code

05 | **TMM** | MFFENet: Multiscale Feature Fusion and Enhancement Network for RGBThermal Urban Road Scene Parsing | [Paper](https://ieeexplore.ieee.org/document/9447924)/[Code](https://wujiezhou.github.io/)

06| **Applied Intelligence** | MMNet: Multi-modal multi-stage network for RGB-T image semantic segmentation | [Paper](https://link.springer.com/article/10.1007/s10489-021-02687-7)/Code

07| **Neurocomputing** | CCAFFMNet: Dual-spectral semantic segmentation network with channel-coordinate attention feature fusion module | [Paper](https://www.sciencedirect.com/science/article/abs/pii/S0925231221017331)/Code

08| **IROS** | HeatNet: Bridging the Day-Night Domain Gap in Semantic Segmentation with Thermal Images | [Paper](https://ieeexplore.ieee.org/abstract/document/9341192)/[Code](http://thermal.cs.uni-freiburg.de/)

## 2022    

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

:triangular_flag_on_post:01 | **AAAI** | Edge-aware guidance fusion network for RGB–thermal scene parsing | [Paper](https://arxiv.org/abs/2112.05144)/[Code](https://github.com/ShaohuaDong2021/EGFNet)

02 | **TIV** | MTANet: Multitask-Aware Network with Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding | [Paper](https://ieeexplore.ieee.org/document/9749834)/[Code](https://github.com/ShaohuaDong2021/MTANet)

:triangular_flag_on_post: 03 | **TITS** | CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers | [Paper](https://arxiv.org/pdf/2203.04838v2.pdf)/[Code](https://github.com/huaaaliu/rgbx_semantic_segmentation)

03 | **ACPR** | ARTSeg: Employing Attention for Thermal Images Semantic Segmentation | [Paper](https://arxiv.org/abs/2111.15257)/Code

04 | **Neurocomputing** | GCNet: Grid-Like Context-Aware Network for RGB-Thermal Semantic Segmentation | [Paper](https://www.sciencedirect.com/science/article/pii/S0925231222009006)/Code

05 | **TCSVT** | RGB-T Semantic Segmentation with Location, Activation, and Sharpening | [Paper](https://ieeexplore.ieee.org/document/9900351/)/[Code](https://github.com/MathLee/LASNet)

06 | **SPL** | GEBNet: Graph-Enhancement Branch Network for RGB-T Scene Parsing | [Paper](https://ieeexplore.ieee.org/abstract/document/9937048/)/[Code](https://github.com/ShaohuaDong2021/GEBNet)

07 | **TCSVT** | A Feature Divide-and-Conquer Network for RGB-T Semantic Segmentation | [Paper](https://ieeexplore.ieee.org/document/9987529)/Code

## 2023  

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **TITS** | Embedded Control Gate Fusion and Attention Residual Learning for RGB–Thermal Urban Scene Parsing | [Paper](https://ieeexplore.ieee.org/document/10041960)/Code

02 | **RAL** | Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks | [Paper](https://ieeexplore.ieee.org/document/10113725)/[Code](https://github.com/freeformrobotics/eaefnet)

03 | **PR** | Complementarity-aware cross-modal feature fusion network for RGB-T semantic segmentation | [Paper](https://www.sciencedirect.com/science/article/pii/S0031320322003624)/Code

04 | **TCSVT** | MMSMCNet: Modal Memory Sharing and Morphological Complementary Networks for RGB-T Urban Scene Semantic Segmentation | [Paper](https://ieeexplore.ieee.org/abstract/document/10123009)/[Code](https://github.com/2021nihao/MMSMCNet)

05 | **TIV** | CACFNet: Cross-Modal Attention Cascaded Fusion Network for RGB-T Urban Scene Parsing | [Paper](https://ieeexplore.ieee.org/abstract/document/10251592)/Code

06 | **TSMC** | DBCNet: Dynamic Bilateral Cross-Fusion Network for RGB-T Urban Scene Understanding in Intelligent Vehicles | [Paper](https://ieeexplore.ieee.org/abstract/document/10217340)/Code

07 | **TCSVT** | SGFNet: Semantic-Guided Fusion Network for RGB-Thermal Semantic Segmentation | [Paper](https://ieeexplore.ieee.org/document/10138593)/[Code](https://github.com/monxxcn/NaDiNet)

08 | **arxiv** | Efficient Multimodal Semantic Segmentation via Dual-Prompt Learning | [Paper](https://arxiv.org/abs/2312.00360)/[Code](https://github.com/ShaohuaDong2021/DPLNet)

09 | **TITS** | A RGB-Thermal Image Segmentation Method Based on Parameter Sharing and Attention Fusion for Safe Autonomous Driving | [Paper](https://ieeexplore.ieee.org/abstract/document/10337777)/Code

10 | **GRSL** | UTFNet: Uncertainty-Guided Trustworthy Fusion Network for RGB-Thermal Semantic Segmentation | [Paper](https://ieeexplore.ieee.org/abstract/document/10273407)/[Code](https://github.com/KustTeamWQW/UTFNet)

11 | **TIM** | SFAF-MA: Spatial Feature Aggregation and Fusion With Modality Adaptation for RGB-Thermal Semantic Segmentation | [Paper](https://ieeexplore.ieee.org/abstract/document/10103760)/[Code](https://github.com/hexunjie/SFAF-MA)

12 | **TIV** | On Exploring Shape and Semantic Enhancements for RGB-X Semantic Segmentation | [Paper](https://ieeexplore.ieee.org/abstract/document/10185113)/[Code](https://github.com/HenonBamboo/SASEM)

## 2024   

**No.** | **Pub.** | **Title** | **Links** 

:-: | :-: | :-  | :-: 

01 | **TMM** | Context-Aware Interaction Network for RGB-T Semantic Segmentation  | [Paper](https://ieeexplore.ieee.org/abstract/document/10379106)/[Code](https://github.com/YingLv1106/CAINet)

--------------------------------------------------------------------------------------

# RGB-T Crowd Counting     

## 2021

**No.** | **Pub.** | **Title** | **Links** |

:-: | :-: | :- | :-:

:triangular_flag_on_post:01 | **CVPR** | Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting | [Paper](https://ieeexplore.ieee.org/document/9578312)/[Code](http://lingboliu.com/RGBT_Crowd_Counting.html)

02 | **IC-NIDC** | I-MMCCN: Improved MMCCN for RGB-T Crowd Counting of Drone Images | [Paper](https://ieeexplore.ieee.org/document/9660586)/Code

## 2022

**No.** | **Pub.** | **Title** | **Links** |

:-: | :-: | :- | :-:

:triangular_flag_on_post:01 | **TITS** | DEFNet: Dual-Branch Enhanced Feature Fusion Network for RGB-T Crowd Counting | [Paper](https://ieeexplore.ieee.org/document/9889192)/[Code](https://github.com/panyi95/DEFNet)

02 | **ISCAS** | TAFNet: A Three-Stream Adaptive Fusion Network for RGB-T Crowd Counting | [Paper](https://ieeexplore.ieee.org/document/9937583)/Code

03 | **ACCV** | Spatio-channel Attention Blocks for Cross-modal Crowd Counting | [Paper](https://arxiv.org/pdf/2210.10392.pdf)/[Code](https://github.com/VCLLab/CSCA)

## 2023

**No.** | **Pub.** | **Title** | **Links** |

:-: | :-: | :- | :-:

01 | **RAL** | Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks | [Paper](https://ieeexplore.ieee.org/document/10113725)/[Code](https://github.com/freeformrobotics/eaefnet)

--------------------------------------------------------------------------------------

# Dataset     

**RGBT SOD Saliency Dataset(VT821,VT1000,VT5000)**  

You can found in [VT800,VT1000,VT5000](https://github.com/lz118/RGBT-Salient-Object-Detection).   


**RGBT Semantic segmentation Dataset(MFNet,PST900,SemanticRT)** 


You can found in [MFNet](https://www.mi.t.u-tokyo.ac.jp/static/projects/mil_multispectral/) and [PST900](https://github.com/ShreyasSkandanS/pst900_thermal_rgb) and [SemanticRT](https://github.com/jiwei0921/SemanticRT). 


**RGBT Crowd Counting Dataset(RGBT-CC)** 


You can found in [RBGT-CC](http://lingboliu.com/RGBT_Crowd_Counting.html)

--------------------------------------------------------------------------------------

# Evaluation     

**RGBT SOD Saliency Evaluation**  


Python version: [here(CPU)](https://github.com/lartpang/PySODEvalToolkit) and [here(GPU)](https://github.com/zyjwuyan/SOD_Evaluation_Metrics).   


Matlab version:  [here(include weighted F)](https://github.com/jiwei0921/Saliency-Evaluation-Toolbox) and [here](http://dpfan.net/d3netbenchmark/). 


**RGBT Semantic segmentation Evaluation**  


Recommend  the evaluation toolbox of [RTFNet](https://github.com/yuxiangsun/RTFNet) or [GMNet](https://github.com/Jinfu0913/GMNet). 


**RGBT Crowd Counting** 


Recommend the evaluation toolbox of [DEFNet](https://github.com/panyi95/DEFNet) or [BL+IADM](http://lingboliu.com/RGBT_Crowd_Counting.html)

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# Other Summary   

**RGBD SOD Summary1：** https://github.com/jiwei0921/SOD-CNNs-based-code-summary-.


**RGBD SOD Summary2：** https://github.com/taozh2017/RGBD-SODsurvey. 


**RGBT SOD Summary：** https://github.com/lz118/RGBT-Salient-Object-Detection. 


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# Acknowledgement   

The collection of this summary is thanks to [Zhun Li](https://github.com/lz118/RGBT-Salient-Object-Detection) , [jinfu Liu](https://github.com/Jinfu0913/GMNet) and [Yi Pan](https://github.com/panyi95/DEFNet). 


The summary template comes from [ji wei](https://github.com/jiwei0921/SOD-CNNs-based-code-summary-).

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## 🏳️‍🌈 Thanks to the above authors for their excellent work！