453 datasets found

The dataset used for the object detection challenge in DAC-SDC 2019.

The dataset used for the low power object detection challenge in DAC-SDC 2019.

A large-scale dataset for object detection and instance segmentation.

The KITTI-C dataset is a robustness benchmark for outdoor monocular depth estimation under data corruptions.

The dataset used in the paper is COCO and D2-City, which are commonly used detection datasets.

Unsupervised multi-object scene decomposition is a fast-emerging problem in representation learning. Despite significant progress in static scenes, models are unable to leverage...

A dataset of 3000 images collected on a public roadway for front seat vehicle occupancy detection.

The dataset used for this problem is presented in Honeybee Segmentation and Tracking Datasets project [Bozek et al., 2017]. One of the contributions of this work is an...

The proposed system is capable of real-time detecting three classes of objects - laptop, phone, and knife - under open carry cases and concealed cases where objects are hidden...

Object detectors are vital to many modern computer vision applications. However, even state-of-the-art object detectors exhibit inconsistent behavior when the input undergoes...

Tiny object detection has become an active area of research because images with tiny targets are common in several important real-world scenarios. However, existing tiny object...

The dataset used for the proposed MoCo-SAS framework, which consists of high-resolution Synthetic Aperture Sonar (SAS) data.

The dataset used in this paper for moving object detection.

The Open Image Dataset V4 is a large-scale object detection dataset with diverse images.

A dataset for training an object detection model to detect symbols in engineering drawings.

A dataset for training an object detection model to detect tables of legends from engineering drawings.

A method of finding and classifying various components and objects in a design diagram, drawing, or planning layout is proposed.

The Scene Graph Generation (SGG) dataset contains 300,000 images with 10,000 object categories.

The dataset used in the paper is a subset of the Caltech Silhouettes database, consisting of 11 images with 42 to 59 pixels in each class.

This dataset contains images paired with multiple human-annotated descriptions in the form of sentences.