49 datasets found

Groups: Object Detection Formats: JSON

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  • NC4K

    Camouflaged object detection (COD) aims to search and segment camouflaged objects from single image.
  • CAMO

    The CAMO dataset is the first COD dataset, containing 1,250 camouflaged images and 1,250 non-camouflaged images.
  • MS COCO dataset

    The MS COCO dataset is a large benchmark for image captioning, containing 328K images with 5 caption descriptions each.
  • ImageNet: A Large-Scale Hierarchical Image Database

    The ImageNet dataset is a large-scale image database that contains over 14 million images, each labeled with one of 21,841 categories.
  • COD10K

    The COD10K dataset is currently the largest challenging dataset for COD, containing 10K images with dense annotations.
  • PASCAL Context

    The PASCAL Context dataset is a benchmark for multi-task learning in computer vision. It contains 10103 images with 5 tasks: semantic segmentation, human body part segmentation,...
  • Confluence: A Robust Non-IOU Alternative to Non-Maxima Suppression in Object ...

    Confluence is a novel non-Intersection over Union (IoU) alternative to Non-Maxima Suppression (NMS) in bounding box post-processing in object detection.
  • KITTI 2012

    KITTI 2012 is a real-world dataset in the outdoor scenario, and contains 194 training and 195 testing stereo image pairs with the size of 376 × 1240.
  • CARLA

    The CARLA dataset is a complex urban-like environment with multi-agent dynamics, pedestrians, intersections, cross-traffic, roundabout, and changing weather conditions.
  • Scannet

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

    The dataset used in this paper for training and testing the KAISA optimizer framework.
  • PASCAL VOC 2007

    Multi-label image recognition is a practical and challenging task compared to single-label image classification.
  • KITTI Vision Benchmark Suite

    The KITTI Vision Benchmark Suite is a dataset used for object detection and tracking in autonomous vehicles.
  • YOLOv2

    The dataset used in the paper is a publicly available dataset for object detection.
  • NYUv2

    Multi-task learning (MTL) research is broadly divided into two categories: one is to learn the correlation between tasks through model structures, and the other is to balance...
  • 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.
  • SemanticPOSS

    A point cloud dataset with large quantity of dynamic instances, consisting of 2,988 real-world scans with point-level annotations.
  • 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...
  • 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...