b'Sicheng Zhao'

Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation

Thanks to large-scale labeled training data, deep neural networks (DNNs)...
11/25/2020 ∙ by Sicheng Zhao, et al. ∙ 7 ∙ share

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Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources

Sentiment analysis of user-generated reviews or comments on products and...
11/17/2020 ∙ by Sicheng Zhao, et al. ∙ 8 ∙ share

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A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Large-scale labeled training datasets have enabled deep neural networks ...
09/01/2020 ∙ by Sicheng Zhao, et al. ∙ 7 ∙ share

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Emotion-Based End-to-End Matching Between Image and Music in Valence-Arousal Space

Both images and music can convey rich semantics and are widely used to i...
08/22/2020 ∙ by Sicheng Zhao, et al. ∙ 0 ∙ share

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Rethinking Distributional Matching Based Domain Adaptation

Domain adaptation (DA) is a technique that transfers predictive models t...
06/23/2020 ∙ by Bo Li, et al. ∙ 16 ∙ share

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Multi-source Domain Adaptation in the Deep Learning Era: A Systematic Survey

In many practical applications, it is often difficult and expensive to o...
02/26/2020 ∙ by Sicheng Zhao, et al. ∙ 38 ∙ share

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An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos

Emotion recognition in user-generated videos plays an important role in ...
02/12/2020 ∙ by Sicheng Zhao, et al. ∙ 0 ∙ share

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Multi-source Domain Adaptation for Visual Sentiment Classification

Existing domain adaptation methods on visual sentiment classification ty...
01/12/2020 ∙ by Chuang Lin, et al. ∙ 30 ∙ share

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Multi-source Distilling Domain Adaptation

Deep neural networks suffer from performance decay when there is domain ...
11/22/2019 ∙ by Sicheng Zhao, et al. ∙ 8 ∙ share

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Multi-source Domain Adaptation for Semantic Segmentation

Simulation-to-real domain adaptation for semantic segmentation has been ...
10/27/2019 ∙ by Sicheng Zhao, et al. ∙ 12 ∙ share

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Sketch-Specific Data Augmentation for Freehand Sketch Recognition

Sketch recognition remains a significant challenge due to the limited tr...
10/14/2019 ∙ by Ying Zheng, et al. ∙ 9 ∙ share

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Affective Computing for Large-Scale Heterogeneous Multimedia Data: A Survey

The wide popularity of digital photography and social networks has gener...
10/03/2019 ∙ by Sicheng Zhao, et al. ∙ 0 ∙ share

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PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion Regression

Existing methods on visual emotion analysis mainly focus on coarse-grain...
09/11/2019 ∙ by Sicheng Zhao, et al. ∙ 4 ∙ share

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Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization without Accessing Target Domain Data

We propose to harness the potential of simulation for the semantic segme...
09/02/2019 ∙ by Xiangyu Yue, et al. ∙ 7 ∙ share

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A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization

State-of-the-art studies have demonstrated the superiority of joint mode...
12/14/2018 ∙ by Sendong Zhao, et al. ∙ 0 ∙ share

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Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different d...
11/05/2018 ∙ by Spyridon Bakas, et al. ∙ 0 ∙ share

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A Novel Domain Adaptation Framework for Medical Image Segmentation

We propose a segmentation framework that uses deep neural networks and i...
10/11/2018 ∙ by Amir Gholami, et al. ∙ 0 ∙ share

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SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

Earlier work demonstrates the promise of deep-learning-based approaches ...
09/22/2018 ∙ by Bichen Wu, et al. ∙ 10 ∙ share

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Unsupervised Domain Adaptation: from Simulation Engine to the RealWorld

Large-scale labeled training datasets have enabled deep neural networks ...
03/24/2018 ∙ by Sicheng Zhao, et al. ∙ 0 ∙ share

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SqueezeNext: Hardware-Aware Neural Network Design

One of the main barriers for deploying neural networks on embedded syste...
03/23/2018 ∙ by Amir Gholami, et al. ∙ 0 ∙ share

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Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions

Neural networks rely on convolutions to aggregate spatial information. H...
11/22/2017 ∙ by Bichen Wu, et al. ∙ 0 ∙ share

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Sicheng Zhao

Featured Co-authors

Yoshua Bengio

Dacheng Tao

Bo Li

Wei Chen

Ting Liu

Yang Zhang

Fei Wang

Chang Liu

Qian Wang

Tat-Seng Chua

Yu Sun

Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation

Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Emotion-Based End-to-End Matching Between Image and Music in Valence-Arousal Space

Rethinking Distributional Matching Based Domain Adaptation

Multi-source Domain Adaptation in the Deep Learning Era: A Systematic Survey

An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos

Multi-source Domain Adaptation for Visual Sentiment Classification

Multi-source Distilling Domain Adaptation

Multi-source Domain Adaptation for Semantic Segmentation

Sketch-Specific Data Augmentation for Freehand Sketch Recognition

Affective Computing for Large-Scale Heterogeneous Multimedia Data: A Survey

PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion Regression

Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization without Accessing Target Domain Data

A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

A Novel Domain Adaptation Framework for Medical Image Segmentation

SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

Unsupervised Domain Adaptation: from Simulation Engine to the RealWorld

SqueezeNext: Hardware-Aware Neural Network Design

Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions