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20202024
most citedEfficientFormer: Vision Transformers at MobileNet Speed

257 citations · 345 across the 15 of their papers we have counts for

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8 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.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★ 6 cited

Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization

Zhengang Li, Mengshu Sun, Alec Lu +9

Vision transformers (ViTs) are emerging with significantly improved accuracy in computer vision tasks. However, their complex architecture and enormous computation/storage demand i…

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…