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20172022
most citedA Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers

498 citations · 1.1k across the 23 of their papers we have counts for

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5 papers · 1 filter

cs.CV2022

RGB-Depth Fusion GAN for Indoor Depth Completion

Haowen Wang, Mingyuan Wang, Zhengping Che +5

The raw depth image captured by the indoor depth sensor usually has an extensive range of missing depth values due to inherent limitations such as the inability to perceive transpa…

cs.CV2021★ 50 cited

LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision

Rui Han, Qinglong Zhang, Chi Harold Liu +3

Deep neural networks (DNNs) have become ubiquitous techniques in mobile and embedded systems for applications such as image/object recognition and classification. The trend of exec…

cs.CV2020★ 3 cited

Domain Conditioned Adaptation Network

Shuang Li, Chi Harold Liu, Qiuxia Lin +4

Tremendous research efforts have been made to thrive deep domain adaptation (DA) by seeking domain-invariant features. Most existing deep DA models only focus on aligning feature r…

cs.CV2020★ 6 cited

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

Xiaolong Ma, Wei Niu, Tianyun Zhang +8

Weight pruning has been widely acknowledged as a straightforward and effective method to eliminate redundancy in Deep Neural Networks (DNN), thereby achieving acceleration on vario…

cs.CV2017★ 177 cited

CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices

Caiwen Ding, Siyu Liao, Yanzhi Wang +13

Large-scale deep neural networks (DNNs) are both compute and memory intensive. As the size of DNNs continues to grow, it is critical to improve the energy efficiency and performanc…