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03/20/2023
Robustifying Token Attention for Vision Transformers
Despite the success of vision transformers (ViTs), they still suffer fro...
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12/13/2022
Boosting Semi-Supervised Learning with Contrastive Complementary Labeling
Semi-supervised learning (SSL) has achieved great success in leveraging ...
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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...
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10/31/2022
Automatic Subspace Evoking for Efficient Neural Architecture Search
Neural Architecture Search (NAS) aims to automatically find effective ar...
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10/14/2022
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets
Designing feasible and effective architectures under diverse computation...
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07/30/2022
Improving Fine-tuning of Self-supervised Models with Contrastive Initialization
Self-supervised learning (SSL) has achieved remarkable performance in pr...
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07/16/2022
Towards Lightweight Super-Resolution with Dual Regression Learning
Deep neural networks have exhibited remarkable performance in image supe...
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01/30/2022
Improving Corruption and Adversarial Robustness by Enhancing Weak Subnets
Deep neural networks have achieved great success in many computer vision...
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07/01/2021
AdaXpert: Adapting Neural Architecture for Growing Data
In real-world applications, data often come in a growing manner, where t...
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06/30/2021
Content-Aware Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have achieved great success due to ...
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03/08/2021
Contrastive Neural Architecture Search with Neural Architecture Comparators
One of the key steps in Neural Architecture Search (NAS) is to estimate ...
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02/27/2021
Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets
Designing feasible and effective architectures under diverse computation...
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02/20/2021
Towards Accurate and Compact Architectures via Neural Architecture Transformer
Designing effective architectures is one of the key factors behind the s...
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01/19/2021
Deep View Synthesis via Self-Consistent Generative Network
View synthesis aims to produce unseen views from a set of views captured...
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01/13/2021
ABS: Automatic Bit Sharing for Model Compression
We present Automatic Bit Sharing (ABS) to automatically search for optim...
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10/10/2020
Double Forward Propagation for Memorized Batch Normalization
Batch Normalization (BN) has been a standard component in designing deep...
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09/21/2020
Conditional Automated Channel Pruning for Deep Neural Networks
Model compression aims to reduce the redundancy of deep networks to obta...
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07/28/2020
Improving Generative Adversarial Networks with Local Coordinate Coding
Generative adversarial networks (GANs) have shown remarkable success in ...
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03/29/2020
Disturbance-immune Weight Sharing for Neural Architecture Search
Neural architecture search (NAS) has gained increasing attention in the ...
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03/16/2020
Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution
Deep neural networks have exhibited promising performance in image super...
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03/10/2020
Hierarchical Neural Architecture Search for Single Image Super-Resolution
Deep neural networks have exhibited promising performance in image super...
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03/01/2020
Joint Wasserstein Distribution Matching
Joint distribution matching (JDM) problem, which aims to learn bidirecti...
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01/04/2020
Discrimination-aware Network Pruning for Deep Model Compression
We study network pruning which aims to remove redundant channels/kernels...
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10/31/2019
NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Designing effective architectures is one of the key factors behind the s...
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03/27/2019
Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis
Generating images via the generative adversarial network (GAN) has attra...
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10/28/2018
Discrimination-aware Channel Pruning for Deep Neural Networks
Channel pruning is one of the predominant approaches for deep model comp...
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09/19/2018
Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss
Deep neural networks have exhibited promising performance in image super...
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06/13/2018
Adversarial Learning with Local Coordinate Coding
Generative adversarial networks (GANs) aim to generate realistic data fr...
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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...
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06/15/2016