453 datasets found

Groups: Object Detection Organizations: No Organization

Filter Results

  • 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.
You can also access this registry using the API (see API Docs).