Sicheng Zhao | DeepAI

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∙ 09/13/2023

Dynamic Causal Disentanglement Model for Dialogue Emotion Detection

Emotion detection is a critical technology extensively employed in diver...

0 Yuting Su, et al. ∙

∙ 07/25/2023

Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion

The emergence of artificial emotional intelligence technology is revolut...

0 James Z. Wang, et al. ∙

∙ 10/27/2021

2nd Place Solution for VisDA 2021 Challenge – Universally Domain Adaptive Image Recognition

The Visual Domain Adaptation (VisDA) 2021 Challenge calls for unsupervis...

0 Haojin Liao, et al. ∙

∙ 08/18/2021

Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies

Humans are emotional creatures. Multiple modalities are often involved w...

0 Sicheng Zhao, et al. ∙

∙ 06/30/2021

Affective Image Content Analysis: Two Decades Review and New Perspectives

Images can convey rich semantics and induce various emotions in viewers....

0 Sicheng Zhao, et al. ∙

∙ 06/30/2021

Multi-Source Domain Adaptation for Object Detection

To reduce annotation labor associated with object detection, an increasi...

0 Xingxu Yao, et al. ∙

∙ 03/19/2021

Computational Emotion Analysis From Images: Recent Advances and Future Directions

Emotions are usually evoked in humans by images. Recently, extensive res...

3 Sicheng Zhao, et al. ∙

∙ 11/25/2020

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

Thanks to large-scale labeled training data, deep neural networks (DNNs)...

7 Sicheng Zhao, et al. ∙

∙ 11/17/2020

Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources

Sentiment analysis of user-generated reviews or comments on products and...

8 Sicheng Zhao, et al. ∙

∙ 09/01/2020

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Large-scale labeled training datasets have enabled deep neural networks ...

7 Sicheng Zhao, et al. ∙

∙ 08/22/2020

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...

0 Sicheng Zhao, et al. ∙

∙ 06/23/2020

Rethinking Distributional Matching Based Domain Adaptation

Domain adaptation (DA) is a technique that transfers predictive models t...

16 Bo Li, et al. ∙

∙ 02/26/2020

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

In many practical applications, it is often difficult and expensive to o...

38 Sicheng Zhao, et al. ∙

∙ 02/12/2020

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 ...

0 Sicheng Zhao, et al. ∙

∙ 01/12/2020

Multi-source Domain Adaptation for Visual Sentiment Classification

Existing domain adaptation methods on visual sentiment classification ty...

30 Chuang Lin, et al. ∙

∙ 11/22/2019

Multi-source Distilling Domain Adaptation

Deep neural networks suffer from performance decay when there is domain ...

8 Sicheng Zhao, et al. ∙

∙ 10/27/2019

Multi-source Domain Adaptation for Semantic Segmentation

Simulation-to-real domain adaptation for semantic segmentation has been ...

12 Sicheng Zhao, et al. ∙

∙ 10/14/2019

Sketch-Specific Data Augmentation for Freehand Sketch Recognition

Sketch recognition remains a significant challenge due to the limited tr...

9 Ying Zheng, et al. ∙

∙ 10/03/2019

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

The wide popularity of digital photography and social networks has gener...

0 Sicheng Zhao, et al. ∙

∙ 09/11/2019

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

Existing methods on visual emotion analysis mainly focus on coarse-grain...

4 Sicheng Zhao, et al. ∙

∙ 09/02/2019

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...

7 Xiangyu Yue, et al. ∙

∙ 12/14/2018

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...

0 Sendong Zhao, et al. ∙

∙ 11/05/2018

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...

0 Spyridon Bakas, et al. ∙

∙ 10/11/2018

A Novel Domain Adaptation Framework for Medical Image Segmentation

We propose a segmentation framework that uses deep neural networks and i...

0 Amir Gholami, et al. ∙

∙ 09/22/2018

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 ...

10 Bichen Wu, et al. ∙

∙ 03/24/2018

Unsupervised Domain Adaptation: from Simulation Engine to the RealWorld

Large-scale labeled training datasets have enabled deep neural networks ...

0 Sicheng Zhao, et al. ∙

∙ 03/23/2018

SqueezeNext: Hardware-Aware Neural Network Design

One of the main barriers for deploying neural networks on embedded syste...

0 Amir Gholami, et al. ∙

∙ 11/22/2017

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

Neural networks rely on convolutions to aggregate spatial information. H...

0 Bichen Wu, et al. ∙

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