Yehui Tang | DeepAI

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495 publications
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158 publications
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142 publications
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95 publications
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∙ 06/01/2023

Can Large Pre-trained Models Help Vision Models on Perception Tasks?

The recent upsurge in pre-trained large models (e.g. GPT-4) has swept ac...

0 Ning Ding, et al. ∙

∙ 03/09/2023

Masked Image Modeling with Local Multi-Scale Reconstruction

Masked Image Modeling (MIM) achieves outstanding success in self-supervi...

0 Haoqing Wang, et al. ∙

∙ 12/13/2022

FastMIM: Expediting Masked Image Modeling Pre-training for Vision

The combination of transformers and masked image modeling (MIM) pre-trai...

0 Jianyuan Guo, et al. ∙

∙ 11/23/2022

GhostNetV2: Enhance Cheap Operation with Long-Range Attention

Light-weight convolutional neural networks (CNNs) are specially designed...

0 Yehui Tang, et al. ∙

∙ 06/01/2022

Vision GNN: An Image is Worth Graph of Nodes

Network architecture plays a key role in the deep learning-based compute...

0 Kai Han, et al. ∙

∙ 04/24/2022

Source-Free Domain Adaptation via Distribution Estimation

Domain Adaptation aims to transfer the knowledge learned from a labeled ...

0 Ning Ding, et al. ∙

∙ 01/04/2022

PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture

Transformer networks have achieved great progress for computer vision ta...

0 Kai Han, et al. ∙

∙ 11/24/2021

An Image Patch is a Wave: Phase-Aware Vision MLP

Different from traditional convolutional neural network (CNN) and vision...

0 Yehui Tang, et al. ∙

∙ 08/30/2021

Hire-MLP: Vision MLP via Hierarchical Rearrangement

This paper presents Hire-MLP, a simple yet competitive vision MLP archit...

0 Jianyuan Guo, et al. ∙

∙ 07/28/2021

Homogeneous Architecture Augmentation for Neural Predictor

Neural Architecture Search (NAS) can automatically design well-performed...

0 Yuqiao Liu, et al. ∙

∙ 07/13/2021

CMT: Convolutional Neural Networks Meet Vision Transformers

Vision transformers have been successfully applied to image recognition ...

0 Jianyuan Guo, et al. ∙

∙ 07/03/2021

Efficient Vision Transformers via Fine-Grained Manifold Distillation

This paper studies the model compression problem of vision transformers....

0 Ding Jia, et al. ∙

∙ 06/30/2021

Augmented Shortcuts for Vision Transformers

Transformer models have achieved great progress on computer vision tasks...

0 Yehui Tang, et al. ∙

∙ 06/05/2021

Patch Slimming for Efficient Vision Transformers

This paper studies the efficiency problem for visual transformers by exc...

0 Yehui Tang, et al. ∙

∙ 04/17/2021

Visual Transformer Pruning

Visual transformer has achieved competitive performance on a variety of ...

0 Mingjian Zhu, et al. ∙

∙ 03/10/2021

Manifold Regularized Dynamic Network Pruning

Neural network pruning is an essential approach for reducing the computa...

0 Yehui Tang, et al. ∙

∙ 03/01/2021

Learning Frequency Domain Approximation for Binary Neural Networks

Binary neural networks (BNNs) represent original full-precision weights ...

0 Yixing Xu, et al. ∙

∙ 12/23/2020

A Survey on Visual Transformer

Transformer is a type of deep neural network mainly based on self-attent...

0 Kai Han, et al. ∙

∙ 10/21/2020

SCOP: Scientific Control for Reliable Neural Network Pruning

This paper proposes a reliable neural network pruning algorithm by setti...

0 Yehui Tang, et al. ∙

∙ 05/14/2020

A Semi-Supervised Assessor of Neural Architectures

Neural architecture search (NAS) aims to automatically design deep neura...

2 Yehui Tang, et al. ∙

∙ 02/23/2020

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks

Deep neural networks often consist of a great number of trainable parame...

72 Yehui Tang, et al. ∙

∙ 09/30/2019

RNAS: Architecture Ranking for Powerful Networks

Neural Architecture Search (NAS) is attractive for automatically produci...

10 Yixing Xu, et al. ∙

∙ 07/13/2019

Bringing Giant Neural Networks Down to Earth with Unlabeled Data

Compressing giant neural networks has gained much attention for their ex...

5 Yehui Tang, et al. ∙

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