b'Yong Guo'

research

∙ 03/20/2023

Robustifying Token Attention for Vision Transformers

Despite the success of vision transformers (ViTs), they still suffer fro...

0 Yong Guo, et al. ∙

research

∙ 12/13/2022

Boosting Semi-Supervised Learning with Contrastive Complementary Labeling

Semi-supervised learning (SSL) has achieved great success in leveraging ...

0 Qinyi Deng, et al. ∙

research

∙ 11/19/2022

Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images

Deep networks have achieved great success in image rescaling (IR) task t...

0 Bingna Xu, et al. ∙

research

∙ 10/31/2022

Automatic Subspace Evoking for Efficient Neural Architecture Search

Neural Architecture Search (NAS) aims to automatically find effective ar...

0 Yaofo Chen, et al. ∙

research

∙ 10/14/2022

Pareto-aware Neural Architecture Generation for Diverse Computational Budgets

Designing feasible and effective architectures under diverse computation...

0 Yong Guo, et al. ∙

research

∙ 07/30/2022

Improving Fine-tuning of Self-supervised Models with Contrastive Initialization

Self-supervised learning (SSL) has achieved remarkable performance in pr...

0 Haolin Pan, et al. ∙

research

∙ 07/16/2022

Towards Lightweight Super-Resolution with Dual Regression Learning

Deep neural networks have exhibited remarkable performance in image supe...

0 Yong Guo, et al. ∙

research

∙ 01/30/2022

Improving Corruption and Adversarial Robustness by Enhancing Weak Subnets

Deep neural networks have achieved great success in many computer vision...

0 Yong Guo, et al. ∙

research

∙ 07/01/2021

AdaXpert: Adapting Neural Architecture for Growing Data

In real-world applications, data often come in a growing manner, where t...

0 Shuaicheng Niu, et al. ∙

research

∙ 06/30/2021

Content-Aware Convolutional Neural Networks

Convolutional Neural Networks (CNNs) have achieved great success due to ...

6 Yong Guo, et al. ∙

research

∙ 03/08/2021

Contrastive Neural Architecture Search with Neural Architecture Comparators

One of the key steps in Neural Architecture Search (NAS) is to estimate ...

0 Yaofo Chen, et al. ∙

research

∙ 02/27/2021

Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets

Designing feasible and effective architectures under diverse computation...

0 Yong Guo, et al. ∙

research

∙ 02/20/2021

Towards Accurate and Compact Architectures via Neural Architecture Transformer

Designing effective architectures is one of the key factors behind the s...

0 Yong Guo, et al. ∙

research

∙ 01/19/2021

Deep View Synthesis via Self-Consistent Generative Network

View synthesis aims to produce unseen views from a set of views captured...

0 Zhuoman Liu, et al. ∙

research

∙ 01/13/2021

ABS: Automatic Bit Sharing for Model Compression

We present Automatic Bit Sharing (ABS) to automatically search for optim...

0 Jing Liu, et al. ∙

research

∙ 10/10/2020

Double Forward Propagation for Memorized Batch Normalization

Batch Normalization (BN) has been a standard component in designing deep...

0 Yong Guo, et al. ∙

research

∙ 09/21/2020

Conditional Automated Channel Pruning for Deep Neural Networks

Model compression aims to reduce the redundancy of deep networks to obta...

35 Yixin Liu, et al. ∙

research

∙ 07/28/2020

Improving Generative Adversarial Networks with Local Coordinate Coding

Generative adversarial networks (GANs) have shown remarkable success in ...

4 Jiezhang Cao, et al. ∙

research

∙ 03/29/2020

Disturbance-immune Weight Sharing for Neural Architecture Search

Neural architecture search (NAS) has gained increasing attention in the ...

0 Shuaicheng Niu, et al. ∙

research

∙ 03/16/2020

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

Deep neural networks have exhibited promising performance in image super...

8 Yong Guo, et al. ∙

research

∙ 03/10/2020

Hierarchical Neural Architecture Search for Single Image Super-Resolution

Deep neural networks have exhibited promising performance in image super...

0 Yong Guo, et al. ∙

research

∙ 03/01/2020

Joint Wasserstein Distribution Matching

Joint distribution matching (JDM) problem, which aims to learn bidirecti...

5 Jiezhang Cao, et al. ∙

research

∙ 01/04/2020

Discrimination-aware Network Pruning for Deep Model Compression

We study network pruning which aims to remove redundant channels/kernels...

21 Jing Liu, et al. ∙

research

∙ 10/31/2019

NAT: Neural Architecture Transformer for Accurate and Compact Architectures

Designing effective architectures is one of the key factors behind the s...

0 Yong Guo, et al. ∙

research

∙ 03/27/2019

Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis

Generating images via the generative adversarial network (GAN) has attra...

24 Yong Guo, et al. ∙

research

∙ 10/28/2018

Discrimination-aware Channel Pruning for Deep Neural Networks

Channel pruning is one of the predominant approaches for deep model comp...

0 Zhuangwei Zhuang, et al. ∙

research

∙ 09/19/2018

Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss

Deep neural networks have exhibited promising performance in image super...

10 Yong Guo, et al. ∙

research

∙ 06/13/2018

Adversarial Learning with Local Coordinate Coding

Generative adversarial networks (GANs) aim to generate realistic data fr...

4 Jiezhang Cao, et al. ∙

research

∙ 11/06/2016

The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs

The depth is one of the key factors behind the great success of convolut...

0 Yong Guo, et al. ∙

research

∙ 06/15/2016

High-speed real-time single-pixel microscopy based on Fourier sampling

Single-pixel cameras based on the concepts of compressed sensing (CS) le...

0 Qiang Guo, et al. ∙

Yong Guo

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