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RFAConv: Innovating Spatial Attention and Standard Convolutional
  Operation

RFAConv: Innovating Spatial Attention and Standard Convolutional Operation

6 April 2023
Xinyu Zhang
Chen Liu
Degang Yang
Tingting Song
Yichen Ye
Ke Li
Ying Song
ArXivPDFHTML

Papers citing "RFAConv: Innovating Spatial Attention and Standard Convolutional Operation"

39 / 39 papers shown
Title
InternImage: Exploring Large-Scale Vision Foundation Models with
  Deformable Convolutions
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
Wenhai Wang
Jifeng Dai
Zhe Chen
Zhenhang Huang
Zhiqi Li
...
Tong Lu
Lewei Lu
Hongsheng Li
Xiaogang Wang
Yu Qiao
VLM
120
683
0
10 Nov 2022
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for
  real-time object detectors
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Chien-Yao Wang
Alexey Bochkovskiy
H. Liao
ObjD
161
6,527
0
06 Jul 2022
A ConvNet for the 2020s
A ConvNet for the 2020s
Zhuang Liu
Hanzi Mao
Chaozheng Wu
Christoph Feichtenhofer
Trevor Darrell
Saining Xie
ViT
159
5,171
0
10 Jan 2022
TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for
  Object Detection on Drone-captured Scenarios
TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios
Xingkui Zhu
Shuchang Lyu
Xu Wang
Qi Zhao
40
1,226
0
26 Aug 2021
EPSANet: An Efficient Pyramid Squeeze Attention Block on Convolutional
  Neural Network
EPSANet: An Efficient Pyramid Squeeze Attention Block on Convolutional Neural Network
Hu Zhang
Keke Zu
Jian Lu
Yuru Zou
Deyu Meng
SSeg
44
211
0
30 May 2021
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Ze Liu
Yutong Lin
Yue Cao
Han Hu
Yixuan Wei
Zheng Zhang
Stephen Lin
B. Guo
ViT
447
21,418
0
25 Mar 2021
Scaling Local Self-Attention for Parameter Efficient Visual Backbones
Scaling Local Self-Attention for Parameter Efficient Visual Backbones
Ashish Vaswani
Prajit Ramachandran
A. Srinivas
Niki Parmar
Blake A. Hechtman
Jonathon Shlens
90
400
0
23 Mar 2021
Involution: Inverting the Inherence of Convolution for Visual
  Recognition
Involution: Inverting the Inherence of Convolution for Visual Recognition
Duo Li
Jie Hu
Changhu Wang
Xiangtai Li
Qi She
Lei Zhu
Tong Zhang
Qifeng Chen
BDL
72
304
0
10 Mar 2021
Coordinate Attention for Efficient Mobile Network Design
Coordinate Attention for Efficient Mobile Network Design
Qibin Hou
Daquan Zhou
Jiashi Feng
80
3,057
0
04 Mar 2021
Bottleneck Transformers for Visual Recognition
Bottleneck Transformers for Visual Recognition
A. Srinivas
Nayeon Lee
Niki Parmar
Jonathon Shlens
Pieter Abbeel
Ashish Vaswani
SLR
357
992
0
27 Jan 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
651
41,103
0
22 Oct 2020
ResNeSt: Split-Attention Networks
ResNeSt: Split-Attention Networks
Hang Zhang
Chongruo Wu
Zhongyue Zhang
Yi Zhu
Yanghua Peng
...
Tong He
Jonas W. Mueller
R. Manmatha
Mu Li
Alex Smola
101
1,477
0
19 Apr 2020
Revisiting Spatial Invariance with Low-Rank Local Connectivity
Revisiting Spatial Invariance with Low-Rank Local Connectivity
Gamaleldin F. Elsayed
Prajit Ramachandran
Jonathon Shlens
Simon Kornblith
60
44
0
07 Feb 2020
Detection and Tracking Meet Drones Challenge
Detection and Tracking Meet Drones Challenge
Pengfei Zhu
Longyin Wen
Dawei Du
Xiao Bian
Heng Fan
Q. Hu
Haibin Ling
AI4TS
46
583
0
16 Jan 2020
GhostNet: More Features from Cheap Operations
GhostNet: More Features from Cheap Operations
Kai Han
Yunhe Wang
Qi Tian
Jianyuan Guo
Chunjing Xu
Chang Xu
99
2,674
0
27 Nov 2019
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural
  Networks
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
Qilong Wang
Banggu Wu
Peng Fei Zhu
P. Li
W. Zuo
Q. Hu
140
4,020
0
08 Oct 2019
Stand-Alone Self-Attention in Vision Models
Stand-Alone Self-Attention in Vision Models
Prajit Ramachandran
Niki Parmar
Ashish Vaswani
Irwan Bello
Anselm Levskaya
Jonathon Shlens
VLM
SLR
ViT
92
1,214
0
13 Jun 2019
Searching for MobileNetV3
Searching for MobileNetV3
Andrew G. Howard
Mark Sandler
Grace Chu
Liang-Chieh Chen
Bo Chen
...
Yukun Zhu
Ruoming Pang
Vijay Vasudevan
Quoc V. Le
Hartwig Adam
345
6,782
0
06 May 2019
Attention Augmented Convolutional Networks
Attention Augmented Convolutional Networks
Irwan Bello
Barret Zoph
Ashish Vaswani
Jonathon Shlens
Quoc V. Le
132
1,014
0
22 Apr 2019
Selective Kernel Networks
Selective Kernel Networks
Xiang Li
Wenhai Wang
Xiaolin Hu
Jian Yang
94
2,035
0
15 Mar 2019
Deformable ConvNets v2: More Deformable, Better Results
Deformable ConvNets v2: More Deformable, Better Results
Xizhou Zhu
Han Hu
Stephen Lin
Jifeng Dai
ObjD
95
2,012
0
27 Nov 2018
Dual Attention Network for Scene Segmentation
Dual Attention Network for Scene Segmentation
J. Fu
Qingbin Liu
Haijie Tian
Yong Li
Yongjun Bao
Zhiwei Fang
Hanqing Lu
SSeg
320
5,108
0
09 Sep 2018
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture
  Design
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
Ningning Ma
Xiangyu Zhang
Haitao Zheng
Jian Sun
174
4,990
0
30 Jul 2018
CBAM: Convolutional Block Attention Module
CBAM: Convolutional Block Attention Module
Sanghyun Woo
Jongchan Park
Joon-Young Lee
In So Kweon
224
16,553
0
17 Jul 2018
BAM: Bottleneck Attention Module
BAM: Bottleneck Attention Module
Jongchan Park
Sanghyun Woo
Joon-Young Lee
In So Kweon
75
1,041
0
17 Jul 2018
Encoder-Decoder with Atrous Separable Convolution for Semantic Image
  Segmentation
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Liang-Chieh Chen
Yukun Zhu
George Papandreou
Florian Schroff
Hartwig Adam
SSeg
439
13,132
0
07 Feb 2018
Squeeze-and-Excitation Networks
Squeeze-and-Excitation Networks
Jie Hu
Li Shen
Samuel Albanie
Gang Sun
Enhua Wu
424
26,500
0
05 Sep 2017
ShuffleNet: An Extremely Efficient Convolutional Neural Network for
  Mobile Devices
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
Xiangyu Zhang
Xinyu Zhou
Mengxiao Lin
Jian Sun
AI4TS
138
6,872
0
04 Jul 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
701
131,652
0
12 Jun 2017
Deformable Convolutional Networks
Deformable Convolutional Networks
Jifeng Dai
Haozhi Qi
Yuwen Xiong
Yi Li
Guodong Zhang
Han Hu
Yichen Wei
201
5,334
0
17 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
297
20,023
0
07 Oct 2016
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable Convolutions
François Chollet
MDE
BDL
PINN
1.4K
14,559
0
07 Oct 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
772
36,813
0
25 Aug 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
You Only Look Once: Unified, Real-Time Object Detection
You Only Look Once: Unified, Real-Time Object Detection
Joseph Redmon
S. Divvala
Ross B. Girshick
Ali Farhadi
ObjD
697
36,958
0
08 Jun 2015
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
465
43,658
0
17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,386
0
04 Sep 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
413
43,667
0
01 May 2014
Network In Network
Network In Network
Min Lin
Qiang Chen
Shuicheng Yan
291
6,275
0
16 Dec 2013
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