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20182022
most citedOne-Two-One Networks for Compression Artifacts Reduction in Remote Sensing

57 citations · 77 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV2022★ 2 cited

End-to-End Zero-Shot HOI Detection via Vision and Language Knowledge Distillation

Mingrui Wu, Jiaxin Gu, Yunhang Shen +3

Most existing Human-Object Interaction~(HOI) Detection methods rely heavily on full annotations with predefined HOI categories, which is limited in diversity and costly to scale fu…

cs.CV2019

Circulant Binary Convolutional Networks: Enhancing the Performance of 1-bit DCNNs with Circulant Back Propagation

Chunlei Liu, Wenrui Ding, Xin Xia +5

The rapidly decreasing computation and memory cost has recently driven the success of many applications in the field of deep learning. Practical applications of deep learning in re…

cs.CV2019

Bayesian Optimized 1-Bit CNNs

Jiaxin Gu, Junhe Zhao, Xiaolong Jiang +4

Deep convolutional neural networks (DCNNs) have dominated the recent developments in computer vision through making various record-breaking models. However, it is still a great cha…

cs.CV2018★ 18 cited

Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation

Jiaxin Gu, Ce Li, Baochang Zhang +4

The advancement of deep convolutional neural networks (DCNNs) has driven significant improvement in the accuracy of recognition systems for many computer vision tasks. However, the…

cs.CV2018★ 57 cited

One-Two-One Networks for Compression Artifacts Reduction in Remote Sensing

Baochang Zhang, Jiaxin Gu, Chen Chen +4

Compression artifacts reduction (CAR) is a challenging problem in the field of remote sensing. Most recent deep learning based methods have demonstrated superior performance over t…