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20222024
most citedEfficientFormer: Vision Transformers at MobileNet Speed

257 citations · 385 across the 22 of their papers we have counts for

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10 papers · 1 filter

cs.CV2023★ 35 cited

SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds

Yanyu Li, Huan Wang, Qing Jin +6

Text-to-image diffusion models can create stunning images from natural language descriptions that rival the work of professional artists and photographers. However, these models ar…

cs.CV2023

Can Adversarial Examples Be Parsed to Reveal Victim Model Information?

Yuguang Yao, Jiancheng Liu, Yifan Gong +4

Numerous adversarial attack methods have been developed to generate imperceptible image perturbations that can cause erroneous predictions of state-of-the-art machine learning (ML)…

cs.CV2022★ 21 cited

Rethinking Vision Transformers for MobileNet Size and Speed

Yanyu Li, Ju Hu, Yang Wen +5

With the success of Vision Transformers (ViTs) in computer vision tasks, recent arts try to optimize the performance and complexity of ViTs to enable efficient deployment on mobile…

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.CV2022★ 1 cited

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model

Shengkun Tang, Yaqing Wang, Zhenglun Kong +6

Large-scale Transformer models bring significant improvements for various downstream vision language tasks with a unified architecture. The performance improvements come with incre…

cs.CV2022★ 2 cited

Data Level Lottery Ticket Hypothesis for Vision Transformers

Xuan Shen, Zhenglun Kong, Minghai Qin +6

The conventional lottery ticket hypothesis (LTH) claims that there exists a sparse subnetwork within a dense neural network and a proper random initialization method called the win…

cs.CV2022★ 2 cited

Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution

Yushu Wu, Yifan Gong, Pu Zhao +7

Deep learning-based super-resolution (SR) has gained tremendous popularity in recent years because of its high image quality performance and wide application scenarios. However, pr…

cs.CV2022

Real-Time Portrait Stylization on the Edge

Yanyu Li, Xuan Shen, Geng Yuan +5

In this work we demonstrate real-time portrait stylization, specifically, translating self-portrait into cartoon or anime style on mobile devices. We propose a latency-driven diffe…

cs.CV2022★ 2 cited

Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization

Yanyu Li, Pu Zhao, Geng Yuan +3

Neural architecture search (NAS) and network pruning are widely studied efficient AI techniques, but not yet perfect. NAS performs exhaustive candidate architecture search, incurri…

cs.CV2022★ 257 cited

EfficientFormer: Vision Transformers at MobileNet Speed

Yanyu Li, Geng Yuan, Yang Wen +5

Vision Transformers (ViT) have shown rapid progress in computer vision tasks, achieving promising results on various benchmarks. However, due to the massive number of parameters an…