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20202026
most citedLearning Best Combination for Efficient N:M Sparsity

23 citations · 132 across the 46 of their papers we have counts for

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Showing 2022 · cs.CVShow all

9 papers · 2 filters

cs.CV2022★ 1 cited

Discriminator-Cooperated Feature Map Distillation for GAN Compression

Tie Hu, Mingbao Lin, Lizhou You +2

Despite excellent performance in image generation, Generative Adversarial Networks (GANs) are notorious for its requirements of enormous storage and intensive computation. As an aw…

cs.CV2022★ 2 cited

Exploring Content Relationships for Distilling Efficient GANs

Lizhou You, Mingbao Lin, Tie Hu +2

This paper proposes a content relationship distillation (CRD) to tackle the over-parameterized generative adversarial networks (GANs) for the serviceability in cutting-edge devices…

cs.CV2022★ 1 cited

SMMix: Self-Motivated Image Mixing for Vision Transformers

Mengzhao Chen, Mingbao Lin, ZhiHang Lin +3

CutMix is a vital augmentation strategy that determines the performance and generalization ability of vision transformers (ViTs). However, the inconsistency between the mixed image…

cs.CV2022★ 2 cited

Meta Architecture for Point Cloud Analysis

Haojia Lin, Xiawu Zheng, Lijiang Li +5

Recent advances in 3D point cloud analysis bring a diverse set of network architectures to the field. However, the lack of a unified framework to interpret those networks makes any…

cs.CV2022

Exploiting the Partly Scratch-off Lottery Ticket for Quantization-Aware Training

Yunshan Zhong, Gongrui Nan, Yuxin Zhang +2

Quantization-aware training (QAT) receives extensive popularity as it well retains the performance of quantized networks. In QAT, the contemporary experience is that all quantized…

cs.CV2022★ 5 cited

LAB-Net: LAB Color-Space Oriented Lightweight Network for Shadow Removal

Hong Yang, Gongrui Nan, Mingbao Lin +4

This paper focuses on the limitations of current over-parameterized shadow removal models. We present a novel lightweight deep neural network that processes shadow images in the LA…