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Construction Equipment Detection Dataset
A dataset for construction equipment detection. -
COCO 2017 and HICO-DET
The dataset used in the paper is COCO 2017 and HICO-DET -
VisDrone2018
The image object detection track on VisDrone2018 provides a dataset of 10,209 images, with 10 categories of pedestrians, vehicles, and other traffic objects annotated. -
MOT16, MOT17, and MOT20 datasets
The MOT16, MOT17, and MOT20 datasets are used for evaluating the proposed One More Check (OMC) tracker. -
MS-COCO 2017 Detection task
The dataset used in the paper is the MS-COCO 2017 Detection task. -
Improved Object-Based Style Transfer with Single Deep Network
The proposed approach uses a single deep network of YOLOv8 for both segmentation and style transfer. -
Synthetic Image Generation for Object Detection using CAD Models
A custom Blender code is used to generate labeled training images containing the rendered CAD model in context. Then, a pretrained object detection model is fine-tuned on the... -
Auto-WCEBleedGen Challenge V1 2023
Auto-WCEBleedGen Challenge V1 2023 dataset for Wireless Capsule Endoscopy bleeding frame classification and detection -
Auto-WCEBleedGen Challenge V2 2024
Auto-WCEBleedGen Challenge V2 2024 dataset for Wireless Capsule Endoscopy bleeding frame classification and detection -
OpenImages dataset V6
The OpenImages dataset V6 contains images with annotations for object detection and instance segmentation tasks. -
VIMER-UFO Benchmark
The VIMER-UFO benchmark dataset consists of 8 computer vision tasks: CPLFW, Market1501, DukeMTMC, MSMT-17, Veri-776, VehicleId, VeriWild, and SOP. -
Microsoft Common Objects in Context (MS COCO)
A well-known dataset for object detection and image segmentation -
ImageNet-52R
The dataset used in the paper is ImageNet-52R, a random subset of ImageNet for object detection. -
ImageNet-52P
The dataset used in the paper is ImageNet-52P, a subset of ImageNet for object detection. -
COCO-stuff dataset
The COCO-stuff dataset contains images of people performing various activities, such as playing sports, riding bicycles, and more.