453 datasets found

The SafeSea dataset is created using the SafeSea method, involving the transformation of 300 calm ocean background images originally sourced from the 'SeaDroneSee' dataset.

A large-scale hierarchical multi-view RGB-D object dataset.

A large-scale 3D database of object instances for scene understanding.

A new multi-view RGB-D dataset for object instance detection and recognition of commonly encountered household objects in realistic settings.

The Occluded Prohibited Items X-ray (OPIXray) image benchmark is a high-quality object detection dataset for security inspection, containing 8885 X-ray images of 5 categories of...

The KITTI object detection benchmark dataset.

ProgS-RCNN: Progressive End-to-End Object Detection in Crowded Scenes

Crowded object detection via copy-paste

CrowdHuman is a challenging benchmark to evaluate the ability of crowded scene detection of detectors, which contains about 15k training images and 4k images for evaluation.

Aerial imagery [2], derived from various sources such as drones, satellites, and high-altitude platforms, plays a pivotal role in numerous real-world applications. One of the...

The COCO test-dev dataset is used for instance segmentation. It contains 20k test-dev images.

Publicly available plant image datasets are crucial in precision agriculture as they reduce the time and effort spent on data collection and preparation. Also, more data enable...

ILSVRC is a large-scale image dataset containing over 1.2 million images across 1,000 classes.

PASCAL VOC 2007 dataset is a widely used dataset for object detection and semantic segmentation. We use all the split sets (training, validation, testing) in the VOC2007 dataset...

The Objects365 dataset is a large-scale object detection dataset containing 365,000 images with 365 categories.

SODA10M contains 10M un-labeled images and 20K labeled images of size 1920 × 1080 with default format of JPEG.

The CODA dataset is a real-world road corner case dataset for object detection in autonomous driving.

PASCAL VOC and MS COCO datasets were used for training.

Object detection using deep neural networks (DNN) has shown excellent performance and has been used in many industrial fields like face recognition, pedestrian detection, and...

The dataset used in the paper for semi-supervised object detection tasks.