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20122023
most citedECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

388 citations · 1.3k across the 31 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.CV2019★ 27 cited

Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention Network

Longyin Wen, Dawei Du, Pengfei Zhu +4

This paper proposes a space-time multi-scale attention network (STANet) to solve density map estimation, localization and tracking in dense crowds of video clips captured by drones…

cs.CV2019★ 388 cited

ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

Qilong Wang, Banggu Wu, Pengfei Zhu +3

Recently, channel attention mechanism has demonstrated to offer great potential in improving the performance of deep convolutional neural networks (CNNs). However, most existing me…

cs.CV2019★ 6 cited

Neural Blind Deconvolution Using Deep Priors

Dongwei Ren, Kai Zhang, Qilong Wang +2

Blind deconvolution is a classical yet challenging low-level vision problem with many real-world applications. Traditional maximum a posterior (MAP) based methods rely heavily on f…

cs.CV2019★ 51 cited

Multi-view Deep Subspace Clustering Networks

Pengfei Zhu, Xinjie Yao, Yu Wang +3

Multi-view subspace clustering aims to discover the inherent structure of data by fusing multiple views of complementary information. Most existing methods first extract multiple t…

cs.CL2019

Semi-interactive Attention Network for Answer Understanding in Reverse-QA

Qing Yin, Guan Luo, Xiaodong Zhu +2

Question answering (QA) is an important natural language processing (NLP) task and has received much attention in academic research and industry communities. Existing QA studies as…

cs.CV2019★ 16 cited

Progressive Image Deraining Networks: A Better and Simpler Baseline

Dongwei Ren, Wangmeng Zuo, Qinghua Hu +2

Along with the deraining performance improvement of deep networks, their structures and learning become more and more complicated and diverse, making it difficult to analyze the co…