55 citations · 109 across the 22 of their papers we have counts for
Showing 2023Show all
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cs.CV2023★ 7 cited
ClusterFormer: Clustering As A Universal Visual Learner
James C. Liang, Yiming Cui, Qifan Wang +3
This paper presents CLUSTERFORMER, a universal vision model that is based on the CLUSTERing paradigm with TransFORMER. It comprises two novel designs: 1. recurrent cross-attention…
cs.CV2023★ 10 cited
E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Cheng Han, Qifan Wang, Yiming Cui +4
As the size of transformer-based models continues to grow, fine-tuning these large-scale pretrained vision models for new tasks has become increasingly parameter-intensive. Paramet…
cs.CV2023★ 1 cited
TransFlow: Transformer as Flow Learner
Yawen Lu, Qifan Wang, Siqi Ma +4
Optical flow is an indispensable building block for various important computer vision tasks, including motion estimation, object tracking, and disparity measurement. In this work,…