June 23, 2021 - Prior studies on Copy-Paste relied on modeling the surrounding visual context for pasting the objects. However, we find that the simple mechanism of pasting objects randomly is good enough and can provide solid gains on top of strong baselines.

paper shows the use of Copy-Paste in improving state-of- the-art instance segmentation models on COCO and LVIS.

August 2, 2022 - In this paper, it is found that the simple mechanism of pasting objects randomly is good enough and can provide solid gains. ... Simple copy and paste method to create new images for training instance segmentation models.

Leveraging data augmentations is a promising direction towards addressing this challenge. Here, we perform a systematic study of the Copy-Paste augmentation (e.g., [13], [12]) for instance segmentation where we randomly paste objects onto an image.

Unofficial implementation of the copy-paste augmentation from Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation.

June 1, 2021 - Here we use ‘copy‐paste’ augmentation to help resolve the generalisation challenge. Copy‐paste augmentation refers to isolating animal ‘segments’ from existing images and pasting the segments onto novel backgrounds to create new, synthetic images that are then used as part of the training data.

December 13, 2020 - Prior studies on Copy-Paste relied on modeling the surrounding visual context for pasting the objects. However, we find that the simple mechanism of pasting objects randomly is good enough and can provide solid gains on top of strong baselines.

May 1, 2022 - 6: Comparison with the state-of-the-art ... for training in instance segmentation tasks. It is simple method but is very useful for improving significantly on top of strong baselines....

June 23, 2021 - Prior studies on Copy-Paste relied on modeling the surrounding visual context for pasting the objects. However, we find that the simple mechanism of pasting objects randomly is good enough and can provide solid gains on top of strong baselines.

December 13, 2020 - Copy-Paste augmentation improves data efficiency and performance for instance segmentation, especially for rare object categories, by randomly pasting objects onto images and is additive with semi-supervised learning methods.

December 13, 2020 - Copy-Paste augmentation significantly improves the performance of state-of-the-art instance segmentation models on the COCO dataset, achieving a new state-of-the-art with 49.1 mask AP and 57.3 box AP.

December 13, 2020 - Prior studies on Copy-Paste relied on modeling the surrounding visual context for pasting the objects. However, we find that the simple mechanism of pasting objects randomly is good enough and can provide solid gains on top of strong baselines.

long-tail and open-vocabulary instance segmentation are · drawing more attention, since they are more realistic settings ... PromptDet (Feng et al., 2022). And the latest work Detic · (Zhou et al., 2022) proposes to utilize image classification · data (i.e., ImageNet-22k(Deng et al., 2009)) to help train · the classifier via image-level supervision. In the following · experiments, we will show our X-Paste, as a simple “Plug · and Play” augmentation strategy without the need of any

A systematic study of the Copy-Paste ... objects onto an image finds that the simple mechanism of pasting objects randomly is good enough and can provide solid gains on top of strong baselines....

December 13, 2020 - Leveragingdata augmentations is ... visual context forpasting the objects. However, we find that the simple mechanism of pastingobjects randomly is good enough and can provide solid gains on top of strongbaselines....

paper：Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation · arXiv：link · 作者提出了一种可用于目标检测和实例分割的数据增强方法：复制粘贴(Copy-Paste)。该方法的主要流程如下： · 随机选择两幅图像； ·

May 17, 2026 - 3 main points ✔️ Use of Copy-Paste algorithm for data augmentation in instance segmentation ✔️ Use of Copy-Paste algorithm in self-supervised (self-training) setting ✔️ New state of the art on COCO and LVIS datasets. Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation written by Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D.

January 19, 2025 - The copy-paste technique augments the data set by generating additional training data via copying segments of the image corresponding to specific objects to be detected or recognized and pasting these onto other images (see below for more details).

This Repo contains the implementation code of "Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation" paper for yolo dataset format. - itstechaj/copy-paste-augmentation