28 datasets found

The OpenImages dataset V6 contains images with annotations for object detection and instance segmentation tasks.

The dataset used in the paper is a synthetic dataset for image-based object detection tasks, specifically instance segmentation and monocular 3D detection.

Po-LarMask: Single shot instance segmentation with polar representation.

Solo: Segmenting objects by locations.

Microsoft COCO: common objects in images.

Instance segmentation is one of the fundamental vision tasks. Recently, fully convolutional instance segmentation methods have drawn much attention as they are often simpler and...

The dataset used in the paper is the COCO object detection and instance segmentation dataset, and the ADE20K semantic segmentation dataset.

The COCO 2014 validation set is used for evaluating the performance of the proposed method.

Yolact dataset contains 100,000 images with 500,000 annotated instances.

The dataset used in this paper is a collection of frames for video coding, with different Quantisation Parameters (QPs) and frame types.

LVIS: A dataset for large vocabulary instance segmentation.

Instance segmentation by refining object detection with semantic and direction features.

The dataset used in this paper for training and testing the KAISA optimizer framework.

LVIS is a large-vocabulary object detection and instance segmentation dataset.

The dataset used in the paper is ImageNet-1K and MS COCO.

The COCO-LT dataset is a long-tail version of the COCO dataset.

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

Vehicle detection in real-time is a challenging and important task. The existing real-time vehicle detection lacks accuracy and speed. Real-time systems must detect and locate...

Semantic segmentation is a crucial and challenging task for image understanding. It aims to predict a dense labeling map for the input image, which assigns each pixel a unique...

Object detection is one of the most foundational computer vision task and is essential for many real-world applications. The object detection pipeline has been developed...