activity
20172026
most citedPatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning

211 citations · 618 across the 23 of their papers we have counts for

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7 papers · 1 filter

cs.CV2022

Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training

Zhenglun Kong, Haoyu Ma, Geng Yuan +12

Vision transformers (ViTs) have recently obtained success in many applications, but their intensive computation and heavy memory usage at both training and inference time limit the…

cs.CV20222 cited

CHEX: CHannel EXploration for CNN Model Compression

Zejiang Hou, Minghai Qin, Fei Sun +7

Channel pruning has been broadly recognized as an effective technique to reduce the computation and memory cost of deep convolutional neural networks. However, conventional pruning…

cs.CV20213 cited

Towards Fast and Accurate Multi-Person Pose Estimation on Mobile Devices

Xuan Shen, Geng Yuan, Wei Niu +5

The rapid development of autonomous driving, abnormal behavior detection, and behavior recognition makes an increasing demand for multi-person pose estimation-based applications, e…

cs.CV2020

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.CV2018

Image Dataset for Visual Objects Classification in 3D Printing

Hongjia Li, Xiaolong Ma, Aditya Singh Rathore +5

The rapid development in additive manufacturing (AM), also known as 3D printing, has brought about potential risk and security issues along with significant benefits. In order to e…

cs.CV2018

C3PO: Database and Benchmark for Early-stage Malicious Activity Detection in 3D Printing

Zhe Li, Xiaolong Ma, Hongjia Li +5

Increasing malicious users have sought practices to leverage 3D printing technology to produce unlawful tools in criminal activities. Current regulations are inadequate to deal wit…