453 datasets found

Groups: Object Detection Formats: JSON

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  • COCO-Full

    The dataset used in the paper for semi-supervised object detection tasks.

  • COCO-Standard

    The dataset used in the paper for semi-supervised object detection tasks.

  • 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.

  • POPE

    The dataset used in this paper is a multimodal large language model (LLaMM) dataset, specifically POPE, which consists of 7 billion parameters and is used for multimodal tasks...

  • 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.

  • Grounding Dino

    Marrying dino with grounded pre-training for open-set object detection.

  • Mask R-CNN dataset

    The dataset used in the paper is a Mask R-CNN dataset for object detection.

  • Feature Pyramid Networks for Object Detection

    Object detection using feature pyramid networks

  • NWPU-RESISC45

    NWPU-RESISC45 dataset was collected from more than 100 countries and regions in the world, consists of 31,500 remote sensing images.

  • VisDrone2019 VID

    Object detection on aerial imagery using CenterNet

  • TrashCan

    A large dataset of images of underwater trash collected from a variety of sources, annotated with bounding boxes and segmentation labels.

  • SemanticPOSS

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

  • COCO Captions

    Object detection is a fundamental task in computer vision, requiring large annotated datasets that are difficult to collect.

  • MS COCO 2014

    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...

  • 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...

  • COCO 2017

    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...

  • Framework for Fast Scalable BNN Inference Using GoogleNet and Transfer Learning

    The work in this project aims to achieve high accuracy in object detection with good real time performance.

  • PSU dataset

    The PSU dataset was collected from two sources: an open dataset of aerial images available on Github and our own images acquired after flying a 3DR SOLO drone equipped with a...

  • Stanford dataset

    The Stanford dataset consists of a large-scale collection of aerial images and videos of a university campus containing various agents (cars, buses, bicycles, golf carts,...

  • PASCAL VOC 2010

    The PASCAL VOC 2010 dataset is an extension of the PASCAL VOC dataset, containing additional images and categories.