TJU stands for Tianjin University, and DHD stands for diverse high-resolution dataset. TJU-DHD is a high-resolution dataset for object detection and pedestrian detection, containing 115,354 high-resolution images (52% images have a resolution of 1624×1200 pixels, and 48% images have a resolution of at least 2,560×1,440 pixels), and 709,330 labeled objects with huge differences in shape and appearance. At the same time, the dataset also provides rich and diverse images in terms of seasonal changes, lighting changes, and weather changes.

Citation

@article{Pang_DHD_TIP_2020, Authors: {Yanwei Pang and Jiale Cao and Yazhao Li and Jin Xie and Hanqing Sun and Jinfeng Gong} title = {TJU-DHD: A Diverse High-Resolution Dataset for Object Detection}, journal = {IEEE Transactions on Image Processing}, year = 2021 } @article{Cao_PDR_TPAMI_2020, author = {Jiale Cao and Yanwei Pang and Jin Xie and Fahad Shahbaz Khan and Ling Shao}, title = {From Handcrafted to Deep Features for Pedestrian Detection: A Survey}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = 2022 }