PaPr: Training-Free One-Step Patch Pruning with Lightweight ConvNets for Faster Inference

24 March 2024

Papers citing "PaPr: Training-Free One-Step Patch Pruning with Lightweight ConvNets for Faster Inference"

6 / 6 papers shown

Title
Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks Yongming Rao Zuyan Liu Wenliang Zhao Jie Zhou Jiwen Lu ViT 39 35 0 04 Jul 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer Sachin Mehta Mohammad Rastegari ViT 189 1,148 0 05 Oct 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 2021
RepVGG: Making VGG-style ConvNets Great Again Xiaohan Ding X. Zhang Ningning Ma Jungong Han Guiguang Ding Jian-jun Sun 117 1,484 0 11 Jan 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,214 0 17 Apr 2017