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A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.
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| 2026-07-31 | 741 |
| 2026-08-01 | 741 |
| 2026-08-06 | 742 |
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# Awesome RGB-T Fusion   A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Salient Object Detection, RGB-T Crowd Counting, RGB-T Fusion Tracking. Welcome to add valuable papers and codes, feel free to star and contact me. Keep updating....🚀 <!-- <details> <summary>Some News: 🆕</summary> 🚀 **2025.08.18 A major update to this repository.** <br> 💎 **2025.07.04 Add one our paper in RGB-T Aerial Object Detection.** <br> 👀 **2025.04.01 Add one dataset in RGB-T-Aerial-Object-Detection (RGBT-Tiny).** <br> 💎 **2025.02.17 Add one dataset-SMOD and some papers in Multispectral Pedestrian Detection.** <br> 👀 **2025.02.12 Add one dataset-MFAD in Multispectral Pedestrian Detection.** <br> 👀 **2024.12.23 Add one TPAMI paper in RGB-T Salient Object Detection.** <br> 💎 **2024.10.31 Add one our paper in Pixel-level Fusion for Detection.** <br> 👀 **2024.10.19 Add one dataset in Multispectral Pedestrian Detection.** <br> 💎 **2024.06.24 Add one our paper and one CVPR paper.** <br> 👀 **2024.05.23 Add one dataset in RGB-T Aerial Object Detection.** <br> 💎 **2024.04.23 Add more papers about RGB-T Salient Object Detection.** <br> 👀 **2024.03.17 Add one CVPR paper.** <br> 💎 **2024.03.15 Add new content about RGB-T Semantic segmentation.** <br> 👀 **2024.03.12 Add one our paper and one CVPR paper.** <br> </details> --> ## Contents 1. [Multispectral Pedestrian Detection](#Multispectral-Pedestrian-Detection) 2. [RGB-T Aerial Object Detection](#RGB-T-Aerial-Object-Detection) 3. [RGB-T Semantic Segmentation](#RGB-T-Semantic-Segmentation) 4. [RGB-T Salient Object Detection](#RGB-T-Salient-Object-Detection) 5. [RGB-T Crowd Counting](#RGB-T-Crowd-Counting) 6. [RGB-T Fusion Tracking](#RGB-T-Fusion-Tracking) -------------------------------------------------------------------------------------- # Multispectral Pedestrian Detection ## Datasets and Tools |Dataset | Years |Modality |Images| Classes| |-------------------------------|-------|-------------|------|--------| |[KAIST](https://soonminhwang.github.io/rgbt-ped-detection/)|2015|RGB, LWIR|95K|1| |[CVC-14](http://adas.cvc.uab.es/elektra/enigma-portfolio/cvc-14-visible-fir-day-night-pedestrian-sequence-dataset/)|2016|RGB, LWIR|8K|1| |[FLIR](https://www.flir.cn/oem/adas/adas-dataset-form/)|2018|RGB, LWIR|20K|5| [FLIR-aligned](https://github.com/zonaqiu/FLIR-align)|2020|RGB, LWIR|5K|3| |[Utokyo](https://www.mi.t.u-tokyo.ac.jp/static/projects/mil_multispectral/)|2017|RGB, NIR, MIR, FIR|7K|5| |[LLVIP](https://bupt-ai-cz.github.io/LLVIP/)|2021| RGB, LWIR|15K|1| |[M<sup>3</sup>FD](https://github.com/dlut-dimt/TarDAL)|2022|RGB, LWIR|4K|6| |[Multi-Spectral Stereo](https://github.com/UkcheolShin/MS2-MultiSpectralStereoDataset)|2023|RGB, NIR, LWIR|195K|4| |[SMOD](https://www.kaggle.com/datasets/zizhaochen6/sjtu-multispectral-object-detection-smod-dataset)|2024|RGB, LWIR|8K|4| |[MMPD](https://github.com/jin-s13/MMPD-Dataset)|2024|RGB, LWIR|260K|1| |[InfraParis](https://ensta-u2is-ai.github.io/infraParis/)|2024| RGB, LWIR, Depth|7K|19| |[MFAD](https://github.com/hukefy/EI2Det)|2025|RGB, LWIR|12K|6| |[RGBT-Ground](https://github.com/crazyxiaoxi/RGBTVG)|2026|RGB, LWIR|40K|5| <!-- |[MMPD](https://github.com/jin-s13/MMPD-Dataset)|2024|RGB, LWIR|1200+|1| --> <!-- [Multi-Spectral Stereo](https://github.com/UkcheolShin/MS2-MultiSpectralStereoDataset), --> ### KAIST Tools - Improved KAIST Testing Annotations provided by Liu et al.[download](https://docs.google.com/forms/d/e/1FAIpQLSe65WXae7J_KziHK9cmX_lP_hiDXe7Dsl6uBTRL0AWGML0MZg/viewform?usp=pp_url&entry.1637202210&entry.1381600
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matched fp:dcc6bc27ba7862d8, llm:Repository description and README: 'A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Salient Object Detection, RGB-T Crowd Counting, RGB-T Fusion Tracking.' Topics include deep-learning, feature-fusion, multispectral-pedestrian-detection, rgb-t-semantic-segmentation, rgbt-tracking, etc.
matched fp:dcc6bc27ba7862d8, llm:Repository description and README: 'A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Salient Object Detection, RGB-T Crowd Counting, RGB-T Fusion Tracking.' Topics include deep-learning, feature-fusion, multispectral-pedestrian-detection, rgb-t-semantic-segmentation, rgbt-tracking, etc.
matched fp:dcc6bc27ba7862d8, llm:Repository description and README: 'A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Salient Object Detection, RGB-T Crowd Counting, RGB-T Fusion Tracking.' Topics include deep-learning, feature-fusion, multispectral-pedestrian-detection, rgb-t-semantic-segmentation, rgbt-tracking, etc.