activity
20192026
most citedFlorence: A New Foundation Model for Computer Vision

342 citations · 689 across the 28 of their papers we have counts for

collaborators
Showing 2021 · cs.CVShow all

7 papers · 2 filters

cs.CV2021★ 13 cited

BEVT: BERT Pretraining of Video Transformers

Rui Wang, Dongdong Chen, Zuxuan Wu +6

This paper studies the BERT pretraining of video transformers. It is a straightforward but worth-studying extension given the recent success from BERT pretraining of image transfor…

cs.CV2021★ 342 cited

Florence: A New Foundation Model for Computer Vision

Lu Yuan, Dongdong Chen, Yi-Ling Chen +20

Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human visio…

cs.CV2021★ 3 cited

MicroNet: Improving Image Recognition with Extremely Low FLOPs

Yunsheng Li, Yinpeng Chen, Xiyang Dai +6

This paper aims at addressing the problem of substantial performance degradation at extremely low computational cost (e.g. 5M FLOPs on ImageNet classification). We found that two f…

cs.CV2021

Mobile-Former: Bridging MobileNet and Transformer

Yinpeng Chen, Xiyang Dai, Dongdong Chen +4

We present Mobile-Former, a parallel design of MobileNet and transformer with a two-way bridge in between. This structure leverages the advantages of MobileNet at local processing…

cs.CV2021★ 64 cited

Dynamic Head: Unifying Object Detection Heads with Attentions

Xiyang Dai, Yinpeng Chen, Bin Xiao +4

The complex nature of combining localization and classification in object detection has resulted in the flourished development of methods. Previous works tried to improve the perfo…

cs.CV2021★ 167 cited

CvT: Introducing Convolutions to Vision Transformers

Haiping Wu, Bin Xiao, Noel Codella +4

We present in this paper a new architecture, named Convolutional vision Transformer (CvT), that improves Vision Transformer (ViT) in performance and efficiency by introducing convo…