395 citations · 1.3k across the 18 of their papers we have counts for
5 papers · 1 filter
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
Golnaz Ghiasi, Yin Cui, Aravind Srinivas +5
Building instance segmentation models that are data-efficient and can handle rare object categories is an important challenge in computer vision. Leveraging data augmentations is a…
Efficient Scale-Permuted Backbone with Learned Resource Distribution
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin +4
Recently, SpineNet has demonstrated promising results on object detection and image classification over ResNet model. However, it is unclear if the improvement adds up when combini…
Spatiotemporal Contrastive Video Representation Learning
Rui Qian, Tianjian Meng, Boqing Gong +4
We present a self-supervised Contrastive Video Representation Learning (CVRL) method to learn spatiotemporal visual representations from unlabeled videos. Our representations are l…
Rethinking Pre-training and Self-training
Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin +4
Pre-training is a dominant paradigm in computer vision. For example, supervised ImageNet pre-training is commonly used to initialize the backbones of object detection and segmentat…
Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset
Menglin Jia, Mengyun Shi, Mikhail Sirotenko +5
In this work we explore the task of instance segmentation with attribute localization, which unifies instance segmentation (detect and segment each object instance) and fine-graine…