activity
20202023
most citedAttention Mechanisms in Computer Vision: A Survey

2.5k citations · 4.7k across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2023★ 24 cited

Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer

Yuzhen Ding, Hongying Feng, Yunze Yang +9

Purpose: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The v…

cs.CV2022★ 6 cited

Discovering Dynamic Functional Brain Networks via Spatial and Channel-wise Attention

Yiheng Liu, Enjie Ge, Mengshen He +6

Using deep learning models to recognize functional brain networks (FBNs) in functional magnetic resonance imaging (fMRI) has been attracting increasing interest recently. However,…

cs.CV2022★ 1 cited

Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning

Chong Ma, Lin Zhao, Yuzhong Chen +15

Learning harmful shortcuts such as spurious correlations and biases prevents deep neural networks from learning the meaningful and useful representations, thus jeopardizing the gen…

cs.CV2022★ 15 cited

Visual Attention Network

Meng-Hao Guo, Cheng-Ze Lu, Zheng-Ning Liu +2

While originally designed for natural language processing tasks, the self-attention mechanism has recently taken various computer vision areas by storm. However, the 2D nature of i…

cs.CV2021★ 2.5k cited

Attention Mechanisms in Computer Vision: A Survey

Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu +7

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim o…

cs.CV2021★ 130 cited

Subdivision-Based Mesh Convolution Networks

Shi-Min Hu, Zheng-Ning Liu, Meng-Hao Guo +4

Convolutional neural networks (CNNs) have made great breakthroughs in 2D computer vision. However, their irregular structure makes it hard to harness the potential of CNNs directly…

cs.CV2021★ 2 cited

Can Attention Enable MLPs To Catch Up With CNNs?

Meng-Hao Guo, Zheng-Ning Liu, Tai-Jiang Mu +3

In the first week of May, 2021, researchers from four different institutions: Google, Tsinghua University, Oxford University and Facebook, shared their latest work [16, 7, 12, 17]…

cs.CV2021★ 83 cited

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks

Meng-Hao Guo, Zheng-Ning Liu, Tai-Jiang Mu +1

Attention mechanisms, especially self-attention, have played an increasingly important role in deep feature representation for visual tasks. Self-attention updates the feature at e…

cs.CV2020★ 1.9k cited

PCT: Point cloud transformer

Meng-Hao Guo, Jun-Xiong Cai, Zheng-Ning Liu +3

The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Tra…

cs.GR2020★ 4 cited

Style-compatible Object Recommendation for Multi-room Indoor Scene Synthesis

Yu He, Yun Cai, Yuan-Chen Guo +5

Traditional indoor scene synthesis methods often take a two-step approach: object selection and object arrangement. Current state-of-the-art object selection approaches are based o…