A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation
By Wuyang Chen, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang and 1 more. 2021
44 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Model Architectures
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Jitendra Malik
- Dacheng Tao
- Ming-Hsuan Yang
- Trevor Darrell
- Xiaogang Wang
- Alan L. Yuille
- Andrew Zisserman
In Model Architectures
- Ross B. Girshick
- Kaiming He
- Quoc V. Le
- Tsung-Yi Lin
- Christoph Feichtenhofer
- Yanghao Li
- Alan L. Yuille
- Ting-Li Chen
Citations in the corpus
- SimpleClick: Interactive Image Segmentation with Simple Vision Transformers (2022, methodology): “Recently, the original ViT is reintroduced as a strong and efficient backbone for semantic segmentation [7] and object detection [23], with the aid of MAE [19] pretraining and window attention for finetuning.”
- Exploring Plain Vision Transformer Backbones for Object Detection (2022, background): “We also compare with UViT [8] which is a recent plain-backbone detection method.”
- A Unified Sequence Interface for Vision Tasks (2022, methodology): “With the invention of Transformers [41], recently being adopted for image classification [11], the research community has seized on the opportunity to unify the backbone design for vision tasks [29, 8, 25].”