941 citations · 5.4k across the 87 of their papers we have counts for
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cs.CV2021★ 133 cited
Swin Transformer V2: Scaling Up Capacity and Resolution
Ze Liu, Han Hu, Yutong Lin +9
Large-scale NLP models have been shown to significantly improve the performance on language tasks with no signs of saturation. They also demonstrate amazing few-shot capabilities l…
cs.CV2021★ 288 cited
VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts
Hangbo Bao, Wenhui Wang, Li Dong +5
We present a unified Vision-Language pretrained Model (VLMo) that jointly learns a dual encoder and a fusion encoder with a modular Transformer network. Specifically, we introduce…
cs.CV2021★ 930 cited
BEiT: BERT Pre-Training of Image Transformers
Hangbo Bao, Li Dong, Songhao Piao +1
We introduce a self-supervised vision representation model BEiT, which stands for Bidirectional Encoder representation from Image Transformers. Following BERT developed in the natu…