HUAWEI Technologies Co., Ltd.

∙ Shenzhen , China ∙ 0 followers

The Huawei Consumer BG is dedicated to delivering the latest technologies to consumers around the world. Huawei unveiled HUAWEI Mate 30 series and Kirin 990 series in 2019, which opens a new era of 5G. Read more about Huawei Consumer Business Group's milestones and achievements over the years in our About Us page

Featured Researchers

Dacheng Tao
210 publications
Jun Wang
156 publications
Qi Tian
104 publications
Hao Chen
100 publications
Jian Zhang
96 publications
Cheng Li
71 publications
Mérouane Debbah
66 publications
Chang Xu
63 publications
Bin Li
61 publications
Bin Liu
60 publications
Bin Wang
59 publications

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks

Deep neural networks often consist of a great number of trainable parame...
02/23/2020 ∙ by Yehui Tang, et al. ∙ 72 ∙ share

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Appending Adversarial Frames for Universal Video Attack

There have been many efforts in attacking image classification models wi...
12/10/2019 ∙ by Zhikai Chen, et al. ∙ 34 ∙ share

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AdderNet: Do We Really Need Multiplications in Deep Learning?

Compared with cheap addition operation, multiplication operation is of m...
12/31/2019 ∙ by Hanting Chen, et al. ∙ 31 ∙ share

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Revisit Knowledge Distillation: a Teacher-free Framework

Knowledge Distillation (KD) aims to distill the knowledge of a cumbersom...
09/25/2019 ∙ by Li Yuan, et al. ∙ 29 ∙ share

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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results

This paper reviews the NTIRE 2020 challenge on real image denoising with...
05/08/2020 ∙ by Abdelrahman Abdelhamed, et al. ∙ 25 ∙ share

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Few-shot Adaptive Faster R-CNN

To mitigate the detection performance drop caused by domain shift, we ai...
03/22/2019 ∙ by Tao Wang, et al. ∙ 24 ∙ share

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Is Fast Adaptation All You Need?

Gradient-based meta-learning has proven to be highly effective at learni...
10/03/2019 ∙ by Khurram Javed, et al. ∙ 24 ∙ share

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RefinedMPL: Refined Monocular PseudoLiDAR for 3D Object Detection in Autonomous Driving

In this paper, we strive for solving the ambiguities arisen by the astou...
11/21/2019 ∙ by Jean Marie Uwabeza Vianney, et al. ∙ 24 ∙ share

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GhostNet: More Features from Cheap Operations

Deploying convolutional neural networks (CNNs) on embedded devices is di...
11/27/2019 ∙ by Kai Han, et al. ∙ 23 ∙ share

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AdvHat: Real-world adversarial attack on ArcFace Face ID system

In this paper we propose a novel easily reproducible technique to attack...
08/23/2019 ∙ by Stepan Komkov, et al. ∙ 21 ∙ share

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Less Is Better: Unweighted Data Subsampling via Influence Function

In the time of Big Data, training complex models on large-scale data set...
12/03/2019 ∙ by Zifeng Wang, et al. ∙ 20 ∙ share

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Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors

The impressive performance of deep convolutional neural networks in sing...
04/14/2020 ∙ by Mateusz Michalkiewicz, et al. ∙ 20 ∙ share

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Generate High-Resolution Adversarial Samples by Identifying Effective Features

As the prevalence of deep learning in computer vision, adversarial sampl...
01/21/2020 ∙ by Sizhe Chen, et al. ∙ 19 ∙ share

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CARS: Continuous Evolution for Efficient Neural Architecture Search

Searching techniques in most of existing neural architecture search (NAS...
09/11/2019 ∙ by Zhaohui Yang, et al. ∙ 17 ∙ share

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Deep Multimodal Neural Architecture Search

Designing effective neural networks is fundamentally important in deep m...
04/25/2020 ∙ by Zhou Yu, et al. ∙ 17 ∙ share

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Real-world attack on MTCNN face detection system

Recent studies proved that deep learning approaches achieve remarkable r...
10/14/2019 ∙ by Edgar Kaziakhmedov, et al. ∙ 16 ∙ share

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Scalable NAS with Factorizable Architectural Parameters

Neural architecture search (NAS) is an emerging topic in machine learnin...
12/31/2019 ∙ by Lanfei Wang, et al. ∙ 16 ∙ share

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Pose Agnostic Cross-spectral Hallucination via Disentangling Independent Factors

The cross-sensor gap is one of the challenges that arise much research i...
09/10/2019 ∙ by Boyan Duan, et al. ∙ 15 ∙ share

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Optimally Combining Classifiers for Semi-Supervised Learning

This paper considers semi-supervised learning for tabular data. It is wi...
06/07/2020 ∙ by Zhiguo Wang, et al. ∙ 15 ∙ share

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AI Benchmark: Running Deep Neural Networks on Android Smartphones

Over the last years, the computational power of mobile devices such as s...
10/02/2018 ∙ by Andrey Ignatov, et al. ∙ 14 ∙ share

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SteReFo: Efficient Image Refocusing with Stereo Vision

Whether to attract viewer attention to a particular object, give the imp...
09/29/2019 ∙ by Benjamin Busam, et al. ∙ 14 ∙ share

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Learning beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling

In real world machine learning applications, testing data may contain so...
10/10/2019 ∙ by Changying Du, et al. ∙ 14 ∙ share

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Coordinates-based Resource Allocation Through Supervised Machine Learning

Appropriate allocation of system resources is essential for meeting the ...
05/13/2020 ∙ by Sahar Imtiaz, et al. ∙ 14 ∙ share

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Distilling portable Generative Adversarial Networks for Image Translation

Despite Generative Adversarial Networks (GANs) have been widely used in ...
03/07/2020 ∙ by Hanting Chen, et al. ∙ 13 ∙ share

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Explore Training of Deep Convolutional Neural Networks on Battery-powered Mobile Devices: Design and Application

The fast-growing smart applications on mobile devices leverage pre-train...
05/26/2020 ∙ by Cong Wang, et al. ∙ 13 ∙ share

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PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning

Deep neural networks have demonstrated cutting edge performance on vario...
12/25/2018 ∙ by Mehdi Jafarnia-Jahromi, et al. ∙ 12 ∙ share

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Discernible Compressed Images via Deep Perception Consistency

Image compression, as one of the fundamental low-level image processing ...
02/17/2020 ∙ by Zhaohui Yang, et al. ∙ 12 ∙ share

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HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens

Neural Architecture Search (NAS) refers to automatically design the arch...
05/29/2020 ∙ by Zhaohui Yang, et al. ∙ 12 ∙ share

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DeepMnemonic: Password Mnemonic Generation via Deep Attentive Encoder-Decoder Model

Strong passwords are fundamental to the security of password-based user ...
06/24/2020 ∙ by Yao Cheng, et al. ∙ 12 ∙ share

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Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning

Social psychology and real experiences show that cognitive consistency p...
12/03/2019 ∙ by Hangyu Mao, et al. ∙ 11 ∙ share

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Adversarial AutoAugment

Data augmentation (DA) has been widely utilized to improve generalizatio...
12/24/2019 ∙ by Xinyu Zhang, et al. ∙ 11 ∙ share

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Image Generation from Freehand Scene Sketches

We introduce the first method for automatic image generation from scene-...
03/05/2020 ∙ by Chengying Gao, et al. ∙ 11 ∙ share

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DeepMark++: CenterNet-based Clothing Detection

The single-stage approach for fast clothing detection as a modification ...
06/01/2020 ∙ by Alexey Sidnev, et al. ∙ 11 ∙ share

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Data-Free Learning of Student Networks

Learning portable neural networks is very essential for computer vision ...
04/02/2019 ∙ by Hanting Chen, et al. ∙ 10 ∙ share

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RNAS: Architecture Ranking for Powerful Networks

Neural Architecture Search (NAS) is attractive for automatically produci...
09/30/2019 ∙ by Yixing Xu, et al. ∙ 10 ∙ share

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Super Resolution Using Segmentation-Prior Self-Attention Generative Adversarial Network

Convolutional Neural Network (CNN) is intensively implemented to solve s...
03/07/2020 ∙ by Yuxin Zhang, et al. ∙ 10 ∙ share

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Multimodal Unified Attention Networks for Vision-and-Language Interactions

Learning an effective attention mechanism for multimodal data is importa...
08/12/2019 ∙ by Zhou Yu, et al. ∙ 9 ∙ share

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Perception as prediction using general value functions in autonomous driving applications

We propose and demonstrate a framework called perception as prediction f...
01/24/2020 ∙ by Daniel Graves, et al. ∙ 9 ∙ share

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Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets

Generative adversarial imitation learning (GAIL) has shown promising res...
05/19/2020 ∙ by Cong Fei, et al. ∙ 9 ∙ share

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Adversarial Domain Adaptation with Domain Mixup

Recent works on domain adaptation reveal the effectiveness of adversaria...
12/04/2019 ∙ by Minghao Xu, et al. ∙ 8 ∙ share

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TensorOpt: Exploring the Tradeoffs in Distributed DNN Training with Auto-Parallelism

A good parallelization strategy can significantly improve the efficiency...
04/16/2020 ∙ by Zhenkun Cai, et al. ∙ 8 ∙ share

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Positive-Unlabeled Compression on the Cloud

Many attempts have been done to extend the great success of convolutiona...
09/21/2019 ∙ by Yixing Xu, et al. ∙ 7 ∙ share

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Phase Collaborative Network for Multi-Phase Medical Imaging Segmentation

Integrating multi-phase information is an effective way of boosting visu...
11/28/2018 ∙ by Huangjie Zheng, et al. ∙ 6 ∙ share

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Aligning Linguistic Words and Visual Semantic Units for Image Captioning

Image captioning attempts to generate a sentence composed of several lin...
08/06/2019 ∙ by Longteng Guo, et al. ∙ 6 ∙ share

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Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System

In real-world question-answering (QA) systems, ill-formed questions, suc...
08/13/2019 ∙ by Ye Liu, et al. ∙ 6 ∙ share

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On Positive-Unlabeled Classification in GAN

This paper defines a positive and unlabeled classification problem for s...
02/04/2020 ∙ by Tianyu Guo, et al. ∙ 6 ∙ share

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Circumventing Outliers of AutoAugment with Knowledge Distillation

AutoAugment has been a powerful algorithm that improves the accuracy of ...
03/25/2020 ∙ by Longhui Wei, et al. ∙ 6 ∙ share

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DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks

Convolution operator is the core of convolutional neural networks (CNNs)...
04/22/2020 ∙ by Yikang Zhang, et al. ∙ 6 ∙ share

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Fitting the Search Space of Weight-sharing NAS with Graph Convolutional Networks

Neural architecture search has attracted wide attentions in both academi...
04/17/2020 ∙ by Xin Chen, et al. ∙ 6 ∙ share

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Learning Instance-wise Sparsity for Accelerating Deep Models

Exploring deep convolutional neural networks of high efficiency and low ...
07/27/2019 ∙ by Chuanjian Liu, et al. ∙ 5 ∙ share

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