453 datasets found

Groups: Object Detection Formats: JSON

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  • Faster-LTN: a neuro-symbolic, end-to-end object detection architecture

    The detection of semantic relationships between objects represented in an image is one of the fundamental challenges in image interpretation. Neural-Symbolic techniques, such as...
  • CHAMELEON: A Dataset for Camouflaged Object Detection

    The CHAMELEON dataset is a dataset for camouflaged object detection.
  • COD10K: A Large-Scale Dataset for Camouflaged Object Detection

    The COD10K dataset is a large-scale dataset for camouflaged object detection.
  • SUN RGB-D

    RGB-D scene recognition approaches often train two standalone backbones for RGB and depth modalities with the same Places or ImageNet pre-training. However, the pre-trained...
  • 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,...
  • FSS-1000

    The FSS-1000 dataset contains 1000 images with 1000 object categories.
  • 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...
  • PASCAL VOC2007 test dataset and VOC2012 trainval datasets

    The dataset used in the paper is PASCAL VOC2007 test dataset and VOC2012 trainval datasets.
  • 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...
  • Visual Genome

    The Visual Genome dataset is a large-scale visual question answering dataset, containing 1.5 million images, each with 15-30 annotated entities, attributes, and relationships.
  • ADE20k

    Semantic segmentation is one of the fundamental prob-lems in computer vision, whose task is to assign a seman-tic label to each pixel of an image so that different classes can...
  • NeRF

    NeRF [33] has demonstrated amazing ability to synthesize images of 3D scenes from novel views. However, they rely upon specialized volumetric rendering algorithms based on ray...
  • COCO2017

    The COCO2017 dataset is used for the trainability experiment, which includes 47,429 images with 210,893 objects.
  • COCO-Thing-Stuff

    The COCO-Thing-Stuff dataset is used for the L2I task, which includes 118,287 training images and 5,000 validation images. Each image is annotated with bounding boxes and...
  • CornerNet

    The CornerNet dataset is a single-stage object detection benchmark.
  • Grid R-CNN

    Grid R-CNN is a novel object detection framework that adopts a grid guided localisation mechanism for accurate object detection.
  • 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.
  • LVIS

    Instance segmentation (IS) is an important computer vision task, aiming at simultaneously predicting the class label and the binary mask for each instance of interest in an image.
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