78 datasets found

Groups: Object Detection Formats: JSON

Filter Results

  • ImageNet, MS COCO, and Pascal VOC datasets

    The dataset used in the paper is ImageNet, MS COCO, and Pascal VOC datasets.

  • ILSVRC

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

  • Objects365

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

  • PASCAL VOC and MS COCO

    PASCAL VOC and MS COCO datasets were used for training.

  • OpenImagesV4

    Object proposal generation models: We study how a detection model trained on a small set of source classes can provide proposals that generalize to unseen object classes.

  • YFCC100M

    The dataset used in the paper is YFCC100M, a large-scale video dataset. The dataset is used for foreground and background patch extraction and object recognition tasks.

  • Pascal VOC

    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...

  • ImageNet Dataset

    Object recognition is arguably the most important problem at the heart of computer vision. Recently, Barbu et al. introduced a dataset called ObjectNet which includes objects in...

  • COCO Dataset

    The COCO dataset is a large-scale dataset for object detection, semantic segmentation, and captioning. It contains 80 object categories and 1,000 image instances per category,...

  • ZeroQ: A Novel Zero Shot Quantization Framework

    Quantization is a promising approach for reducing the inference time and memory footprint of neural networks. However, most existing quantization methods require access to the...

  • OpenImages

    Large-scale vision-and-language models trained on curated and web-scrapped data have led to significant improvements over task-specific models when transferred to downstream...

  • MS-COCO

    Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

  • LSUN

    The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.

  • Microsoft COCO

    The Microsoft COCO dataset was used for training and evaluating the CNNs because it has become a standard benchmark for testing algorithms aimed at scene understanding and...

  • ImageNet Large Scale Visual Recognition Challenge

    A benchmark for low-shot recognition was proposed by Hariharan & Girshick (2017) and consists of a representation learning phase without access to the low-shot classes and a...

  • DOTA

    The DOTA dataset is a large aerial image dataset for oriented objects detection which contains 2806 images with the size ranges from 800 × 800 to 4000 × 4000 and 188282...

  • ImageNet-1k

    The dataset used in the paper is not explicitly described, but it is mentioned that the authors used it for language modeling and image classification tasks.

  • COCO

    Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...