70 datasets found

The proposed method, dubbed Dynamic Hyperpixel Flow, learns to compose hypercolumn features on the fly by selecting a small number of relevant layers from a deep convolutional...

The Medical Segmentation Decathlon dataset is a benchmark for medical image segmentation, containing 131 CT volumes.

A comprehensive benchmark for multi-subject driven text-to-video generation, covering a wide range of subject categories and diverse subject pairs.

The dataset used for training and testing the proposed RGBD-based obstacle avoidance system for visually impaired people.

The COCO 2017 detection benchmark dataset is used for evaluating the proposed TSP-FCOS and TSP-RCNN models.

A large-scale benchmark for evaluating the brain-likeness of neural networks.

The multimodal brain tumor image segmentation benchmark (brats).

The 3DMatch [26] is a well-known indoor registration dataset of 62 scenes captured by RGBD sensor.

The MS COCO 2014 Dataset contains images of 91 object categories, which contains 82783 training images, 40504 validation images and 40775 testing images.

The MS COCO detection dataset is a large-scale object detection benchmark.

QuixBugs is a multi-lingual program repair benchmark set based on the Quixey Challenge.

The Moving AI benchmark dataset contains maps of various sizes and complexity.

MorphBench is the first benchmark dataset for assessing image morphing of general objects.

The DAVIS dataset is a widely used dataset for video-related tasks, consisting of approximately 2000 frames from 26 human-centric scenarios.

The TrackingNet dataset is a benchmark for visual tracking, containing 511 video sequences with varying difficulties.

The Tiny YOLO dataset is a benchmark for object detection.

The dataset used in the paper is a publicly available dataset for object detection.

Scene segmentation in images is a fundamental yet challenging problem in visual content understanding, which is to learn a model to assign every image pixel to a categorical label.

The PASCAL VOC2007 dataset is a benchmark for object detection and image classification.

The RefCOCOg dataset is a reconstructed dataset of the MS-COCO dataset, containing 85,474 referring expressions for 54,822 objects in 26,711 images.