datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
real-infrared-maritime-vessel-dataset
Real Infrared Maritime Vessel Dataset
Real infrared imagery of maritime vessels.
The dataset is provided in three forms — full-frame detection images, per-object classification crops, and a hand-curated subset.
Classes (7): liner, bulk carrier, warship, sailboat, canoe, container ship, fishing boat.
Layout
real-infrared-maritime-vessel-dataset/
├── original/ Full-frame IR images + XML bounding-box labels (detection)
│ ├── images/{train,test}/*.jpg… See the full description on the dataset page: https://huggingface.co/datasets/hanchong/real-infrared-maritime-vessel-dataset.Optical-SAR-Infrared
MMDiff: Multi-modal Remote Sensing Image Generation via Cross-Modality Spatial Feature Transfer
ISPRS 2026 🔥
Haojun Tang1 · Wenda Zhao1,* · Hengshuai Cui1 · Haipeng Wang2
1 Dalian University of Technology2 Unit 92728 of PLA
* Corresponding author:
Abstract
Collecting spatially consistent multi-modal remote sensing (MMRS) images remains challenging due to different sensors vary in the imaging principles and acquisition times. This hinders… See the full description on the dataset page: https://huggingface.co/datasets/XinRan-Tang/Optical-SAR-Infrared.real-infrared-maritime-vessel-dataset
Real Infrared Maritime Vessel Dataset
Real infrared imagery of maritime vessels.
The dataset is provided in three forms — full-frame detection images, per-object classification crops, and a hand-curated subset.
Classes (7): liner, bulk carrier, warship, sailboat, canoe, container ship, fishing boat.
Layout
real-infrared-maritime-vessel-dataset/
├── original/ Full-frame IR images + XML bounding-box labels (detection)
│ ├── images/{train,test}/*.jpg… See the full description on the dataset page: https://huggingface.co/datasets/Abin0008/real-infrared-maritime-vessel-dataset.real-infrared-maritime-vessel-dataset
Real Infrared Maritime Vessel Dataset
Real infrared imagery of maritime vessels.
The dataset is provided in three forms — full-frame detection images, per-object classification crops, and a hand-curated subset.
Classes (7): liner, bulk carrier, warship, sailboat, canoe, container ship, fishing boat.
Layout
real-infrared-maritime-vessel-dataset/
├── original/ Full-frame IR images + XML bounding-box labels (detection)
│ ├── images/{train,test}/*.jpg… See the full description on the dataset page: https://huggingface.co/datasets/liujinfansjtu89/real-infrared-maritime-vessel-dataset.synthetic-infrared-maritime-vessel-dataset-flux2klein
Synthetic Infrared Maritime Vessel Dataset (FLUX2-Klein)
RGB maritime vessel images translated to synthetic infrared via a DreamBooth-finetuned FLUX.2-Klein-4B.
Layout
synthetic-infrared-maritime-vessel-dataset-flux2klein/
├── in-distribution/
│ ├── train/{C00,C02,...}/*.jpg
│ ├── val/{C00,C02,...}/*.jpg
│ ├── test/{C00,C02,...}/*.jpg
│ ├── labels.txt
│ └── selected-metadata-{train,val,test}.json
└── out-of-distribution/
├── val/{C01,C03,C06… See the full description on the dataset page: https://huggingface.co/datasets/hanchong/synthetic-infrared-maritime-vessel-dataset-flux2klein.synthetic-infrared-maritime-vessel-dataset-flux2klein-degraded
Degraded Infrared Maritime Vessel Dataset
Real-ESRGAN's synthetic image degradation pipeline applied to the FLUX2-Klein synthetic infrared dataset.
Layout
synthetic-infrared-maritime-vessel-dataset-flux2klein-degraded/
├── in-distribution/
│ ├── train/{C00,C02,...}/*.jpg
│ ├── val/{C00,C02,...}/*.jpg
│ ├── test/{C00,C02,...}/*.jpg
│ ├── labels.txt
│ └── selected-metadata-{train,val,test}.json
└── out-of-distribution/
├── val/{C01,C03,C06,C16}/*.jpg… See the full description on the dataset page: https://huggingface.co/datasets/hanchong/synthetic-infrared-maritime-vessel-dataset-flux2klein-degraded.real-infrared-maritime-vessel-dataset-super-resolved
Real Infrared Maritime Vessel Dataset (Super-Resolved, HYPIR)
HYPIR-restored crops of the real infrared maritime vessel dataset (cropped/), with vs without a fixed class-name text prompt guiding restoration.
Layout
real-infrared-maritime-vessel-dataset-super-resolved/
├── w_cat_prompt/ restored with prompt: "infrared image of a <class-name> on sea water"
│ ├── labels.txt, {train,val,test}.csv
│ ├── train/{0..6}/*.png 25,045
│ ├── val/{0..6}/*.png… See the full description on the dataset page: https://huggingface.co/datasets/hanchong/real-infrared-maritime-vessel-dataset-super-resolved.4484-People-Multi-race-Infrared-Face-Recognition-Data
Description
4,484명 규모의 다인종 적외선 얼굴 인식 데이터셋입니다. 데이터는 실내 및 실외 환경에서 수집되었으며, 남성과 여성을 모두 포함합니다. 인종은 아시아인, 흑인, 백인, 갈색 피부 인구로 구성되어 있습니다. 연령은 청소년부터 고령층까지 다양한 범위로 구성되어 있으며, 청년층과 중년층이 주를 이룹니다. 데이터 수집에는 DV-DH4,044S305AD를 사용했습니다. 다양한 연령대, 얼굴 자세 및 환경을 포함하여 데이터의 다양성을 확보했습니다. 본 데이터셋은 적외선 얼굴 인식 등의 작업에 활용할 수 있습니다.
데이터 수집, 저장 및 활용 전 과정에서 개인정보 보호 및 관련 법규를 엄격하게 준수하며, 사용자의 개인정보와 법적 권리를 보호합니다. 본 데이터셋은 GDPR, CCPA, PIPL을 준수합니다.
자세한 내용은 아래 링크를 참고해 주세요:… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata-kr/4484-People-Multi-race-Infrared-Face-Recognition-Data.infrared_benchmarkInfrared_visibleinfrared_datasetInfraRed_Photos_Annotated_for_Birds_DetectionDataset created using Intel Geti. This dataset was created while working on Master thesis at Warsaw University of Technology. Code and more additional info about the project is available here: DecisionSystemFeeder.
The model based on YOLO trained on this dataset using Intel Geti was published here: Infrared_Bird_Detection
InfraredSolarModulesinfrared-TN460U