He, Xiaodong

MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition

Guo, Y., Zhang, L., Hu, Y., He, X., & Gao, J. (2016) · Lecture Notes in Computer Science

Face recognition and analysisFace and Expression Recognition

Cited by 2,122

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

Xu, T., Zhang, P., Huang, Q., Zhang, H., Gan, Z., Huang, X., & He, X. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 1,923

Stacked Cross Attention for Image-Text Matching

Lee, K.-H., Chen, X., Hua, G., Hu, H., & He, X. (2018) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,402

Recent advances in deep learning for speech research at Microsoft

Deng, L., Li, J., Huang, J.-T., Yao, K., Yu, D., Seide, F., Seltzer, M., Zweig, G., He, X., Williams, J., et al. (2013) · 2013 IEEE International Conference on Acoustics, Speech and Signal Processing

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 801

A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories

Mostafazadeh, N., Chambers, N., He, X., Parikh, D., Batra, D., Vanderwende, L., Kohli, P., & Allen, J. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 598

Multimodal intelligence: Representation learning, information fusion, and applications

Zhang, C., Yang, Z., He, X., & Deng, L. (2020) · IEEE Journal of Selected Topics in Signal Processing

Multimodal Machine Learning ApplicationsAdvanced Image Fusion Techniques

Cited by 511

Deep Learning with Low Precision by Half-Wave Gaussian Quantization

Cai, Z., He, X., Sun, J., & Vasconcelos, N. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 498

Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval

Liu, X., Gao, J., He, X., Deng, L., Duh, K., & Wang, Y.-Y. (2015) · Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingInformation Retrieval and Search Behavior

Cited by 395

Generating Natural Questions About an Image

Mostafazadeh, N., Misra, I., Devlin, J., Mitchell, M., He, X., & Vanderwende, L. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 270

Select, Answer and Explain: Interpretable Multi-Hop Reading Comprehension over Multiple Documents

Tu, M., Huang, K., Wang, G., Huang, J., He, X., & Zhou, B. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Topic ModelingInformation Retrieval and Search Behavior

Cited by 136

Conversational AI Systems for Social Good: Opportunities and Challenges

Qi, P., Huang, J., Wu, Y., He, X., & Zhou, B. (2021) · arXiv

Speech and dialogue systemsEthics and Social Impacts of AI

Cited by 3

ChartMaster: Advancing Chart-to-Code Generation with Real-World Charts and Chart Similarity Reinforcement Learning

Tan, W., Cao, Q., Xue, C., Zhan, Y., Ding, C., & He, X. (2025) · arXiv

Multimodal Machine Learning ApplicationsSoftware Engineering Research

Cited by 0