One-Shot Object Detection
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Benchmarks
PASCAL VOC 2012 val
Most implemented
Quasi-Dense Similarity Learning for Multiple Object Tracking
One-Shot Instance Segmentation
Simple Open-Vocabulary Object Detection with Vision Transformers
One-Shot Object Detection with Co-Attention and Co-Excitation
DroNet: Efficient convolutional neural network detector for real-time UAV applications
Detect Everything with Few Examples
Papers
Learning Gaussian Data Augmentation in Feature Space for One-shot Object Detection in Manga
We tackle one-shot object detection in Japanese Manga. The rising global popularity of Japanese manga has made the object detection of character faces increasingly important, with potential applications such as automatic…
ColorizationData AugmentationObjectobject-detection+2Detect Everything with Few Examples
Few-shot object detection aims at detecting novel categories given only a few example images. It is a basic skill for a robot to perform tasks in open environments. Recent methods focus on finetuning strategies, with com…
Binary ClassificationCross-Domain Few-Shot Object DetectionFew-Shot Object DetectionObject+4Adaptive Base-class Suppression and Prior Guidance Network for One-Shot Object Detection
One-shot object detection (OSOD) aims to detect all object instances towards the given category specified by a query image. Most existing studies in OSOD endeavor to explore effective cross-image correlation and alleviat…
object-detectionObject DetectionOne-Shot Object DetectionOne-Shot Doc Snippet Detection: Powering Search in Document Beyond Text
Active consumption of digital documents has yielded scope for research in various applications, including search. Traditionally, searching within a document has been cast as a text matching problem ignoring the rich layo…
document understandingobject-detectionObject DetectionOne-Shot Object Detection+2Identification of Binary Neutron Star Mergers in Gravitational-Wave Data Using YOLO One-Shot Object Detection
We demonstrate the application of the YOLOv5 model, a general purpose convolution-based single-shot object detection model, in the task of detecting binary neutron star (BNS) coalescence events from gravitational-wave da…
object-detectionObject DetectionOne-Shot Object DetectionSynthetic Data GenerationSimple Open-Vocabulary Object Detection with Vision Transformers
Combining simple architectures with large-scale pre-training has led to massive improvements in image classification. For object detection, pre-training and scaling approaches are less well established, especially in the…
Described Object Detectionimage-classificationImage ClassificationObject+4