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10 Best Object Detection Datasets [2023]

Object detection is an important field in computer vision and machine learning, where the goal is to detect objects and localize them in an image or video. The accuracy and performance of object detection models depend heavily on the quality and diversity of the training data. In this article, we will be discussing the top 10 object detection datasets that are widely used by researchers and practitioners in the field. These datasets cover a range of challenges, from small objects in cluttered scenes to large-scale object detection in aerial images, and provide a valuable resource for evaluating and improving object detection models. Whether you are a machine learning researcher or practitioner, these datasets will give you a good starting point for developing and testing your object detection algorithms.

Dataset NameDescriptionReference PaperDownload Link
COCO (Common Objects in Context)A large-scale dataset for object detection and segmentation, containing over 330K images annotated with 80 object categories.T. Lin et al., “Microsoft COCO: Common Objects in Context”, ECCV 2014.http://cocodataset.org/#download
PASCAL VOCA benchmark dataset for object detection and segmentation, containing over 20K images annotated with 20 object categories.M. Everingham et al., “The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results”, IJCV 2014.http://host.robots.ox.ac.uk/pascal/VOC/voc2012/
ImageNetA large-scale dataset for image classification and object recognition, containing over 1.2 million images labeled with 1000 object categories.J. Deng et al., “ImageNet: A Large-Scale Hierarchical Image Database”, CVPR 2009.http://image-net.org/download-images
OpenImagesA large-scale dataset for object detection and segmentation, containing over 9 million images annotated with 600 object categories.T. Kuznetsova et al., “OpenImages: A Public Dataset for Large-Scale Multi-Label Image Classification”, CVPR 2018.https://storage.googleapis.com/openimages/web/index.html
ILSVRC (ImageNet Large Scale Visual Recognition Challenge)A benchmark competition for image classification and object recognition, using the ImageNet dataset as the test bed.J. Deng et al., “ImageNet: A Large-Scale Hierarchical Image Database”, CVPR 2009.http://image-net.org/challenges/LSVRC/
CityscapesA large-scale dataset for semantic segmentation of urban scenes, containing over 5,000 images annotated with 30 object categories.M. Cordts et al., “The Cityscapes Dataset for Semantic Urban Scene Understanding”, CVPR 2016.https://www.cityscapes-dataset.com/
Udacity Object Detection DatasetA dataset for object detection in self-driving cars, containing over 10,000 images collected from a moving vehicle.N/Ahttps://github.com/udacity/self-driving-car
KITTI Vision Benchmark SuiteA dataset for computer vision research, focusing on tasks like object detection, semantic segmentation, optical flow, and stereo. The dataset consists of over 7,000 images collected from a moving vehicle in urban and rural environments.N/Ahttp://www.cvlibs.net/datasets/kitti/
AVA (Atmospheric Vehicle Annotations)A large-scale dataset for object detection in video, containing over 1 million annotated instances of vehicles in over 1,500 video clips.N/Ahttps://research.google.com/ava/
DOTA (Dataset for Object Detection in Aerial Images)A large-scale dataset for object detection in aerial images, containing over 2,800 images annotated with 15 object categories.N/Ahttps://captain-whu.github.io/DOTA/dataset.html
Visual GenomeA large-scale dataset for visual question answering, image captioning, and visual relationship detection, containing over 108,000 images annotated with objects, attributes, relationships, and captions.K. Krishnavisual et al., “Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations”, IJCV 2016.https://visualgenome.org/api/v0/api_home.html

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