Search Results for author: Jianyuan Guo

Found 19 papers, 14 papers with code

Brain-inspired Multilayer Perceptron with Spiking Neurons

no code implementations28 Mar 2022 Wenshuo Li, Hanting Chen, Jianyuan Guo, Ziyang Zhang, Yunhe Wang

However, due to the simplicity of their structures, the performance highly depends on the local features communication machenism.

GhostNets on Heterogeneous Devices via Cheap Operations

2 code implementations10 Jan 2022 Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chunjing Xu, Enhua Wu, Qi Tian

The proposed C-Ghost module can be taken as a plug-and-play component to upgrade existing convolutional neural networks.

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

1 code implementation4 Jan 2022 Kai Han, Jianyuan Guo, Yehui Tang, Yunhe Wang

We hope this new baseline will be helpful to the further research and application of vision transformer.

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

4 code implementations24 Nov 2021 Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Yanxi Li, Chao Xu, Yunhe Wang

To dynamically aggregate tokens, we propose to represent each token as a wave function with two parts, amplitude and phase.

Image Classification Object Detection +1

Hire-MLP: Vision MLP via Hierarchical Rearrangement

3 code implementations30 Aug 2021 Jianyuan Guo, Yehui Tang, Kai Han, Xinghao Chen, Han Wu, Chao Xu, Chang Xu, Yunhe Wang

Previous vision MLPs such as MLP-Mixer and ResMLP accept linearly flattened image patches as input, making them inflexible for different input sizes and hard to capture spatial information.

Image Classification Object Detection +1

CMT: Convolutional Neural Networks Meet Vision Transformers

7 code implementations13 Jul 2021 Jianyuan Guo, Kai Han, Han Wu, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang

Vision transformers have been successfully applied to image recognition tasks due to their ability to capture long-range dependencies within an image.

Positive-Unlabeled Data Purification in the Wild for Object Detection

no code implementations CVPR 2021 Jianyuan Guo, Kai Han, Han Wu, Chao Zhang, Xinghao Chen, Chunjing Xu, Chang Xu, Yunhe Wang

In this paper, we present a positive-unlabeled learning based scheme to expand training data by purifying valuable images from massive unlabeled ones, where the original training data are viewed as positive data and the unlabeled images in the wild are unlabeled data.

Knowledge Distillation Object Detection

Patch Slimming for Efficient Vision Transformers

no code implementations5 Jun 2021 Yehui Tang, Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chao Xu, DaCheng Tao

We first identify the effective patches in the last layer and then use them to guide the patch selection process of previous layers.

Distilling Object Detectors via Decoupled Features

1 code implementation CVPR 2021 Jianyuan Guo, Kai Han, Yunhe Wang, Han Wu, Xinghao Chen, Chunjing Xu, Chang Xu

To this end, we present a novel distillation algorithm via decoupled features (DeFeat) for learning a better student detector.

Knowledge Distillation Object Detection

Transformer in Transformer

10 code implementations NeurIPS 2021 Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing Xu, Yunhe Wang

In this paper, we point out that the attention inside these local patches are also essential for building visual transformers with high performance and we explore a new architecture, namely, Transformer iN Transformer (TNT).

Fine-Grained Image Classification

A Survey on Vision Transformer

no code implementations23 Dec 2020 Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, DaCheng Tao

Transformer, first applied to the field of natural language processing, is a type of deep neural network mainly based on the self-attention mechanism.

Image Classification

HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens

1 code implementation CVPR 2021 Zhaohui Yang, Yunhe Wang, Xinghao Chen, Jianyuan Guo, Wei zhang, Chao Xu, Chunjing Xu, DaCheng Tao, Chang Xu

To achieve an extremely fast NAS while preserving the high accuracy, we propose to identify the vital blocks and make them the priority in the architecture search.

Neural Architecture Search

Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection

1 code implementation CVPR 2020 Jianyuan Guo, Kai Han, Yunhe Wang, Chao Zhang, Zhaohui Yang, Han Wu, Xinghao Chen, Chang Xu

To this end, we propose a hierarchical trinity search framework to simultaneously discover efficient architectures for all components (i. e. backbone, neck, and head) of object detector in an end-to-end manner.

Image Classification Neural Architecture Search +1

GhostNet: More Features from Cheap Operations

13 code implementations CVPR 2020 Kai Han, Yunhe Wang, Qi Tian, Jianyuan Guo, Chunjing Xu, Chang Xu

Deploying convolutional neural networks (CNNs) on embedded devices is difficult due to the limited memory and computation resources.

Image Classification

Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification

1 code implementation ICCV 2019 Jianyuan Guo, Yuhui Yuan, Lang Huang, Chao Zhang, Jinge Yao, Kai Han

On the other hand, there still exist many useful contextual cues that do not fall into the scope of predefined human parts or attributes.

Human Parsing Person Re-Identification

Attribute-Aware Attention Model for Fine-grained Representation Learning

1 code implementation2 Jan 2019 Kai Han, Jianyuan Guo, Chao Zhang, Mingjian Zhu

Based on the considerations above, we propose a novel Attribute-Aware Attention Model ($A^3M$), which can learn local attribute representation and global category representation simultaneously in an end-to-end manner.

Fine-Grained Image Classification Image Retrieval +2

OCNet: Object Context Network for Scene Parsing

8 code implementations4 Sep 2018 Yuhui Yuan, Lang Huang, Jianyuan Guo, Chao Zhang, Xilin Chen, Jingdong Wang

To capture richer context information, we further combine our interlaced sparse self-attention scheme with the conventional multi-scale context schemes including pyramid pooling~\citep{zhao2017pyramid} and atrous spatial pyramid pooling~\citep{chen2018deeplab}.

Scene Parsing Semantic Segmentation

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