Yueyu HU, 胡越予

Ph.D. Student, New York University

yyhu AT nyu·edu

About Me

I am currently pursuing a Ph.D. with Prof. Yao Wang at NYU Video Lab. I received a master's degree in computer science at Peking University, advised by Prof. Jiaying Liu at STRUCT. My research interests include computer vision, machine learning and image/video compression. I am also interested in photography, trains and railways, meteorology, science-fiction and computer network development.

WHIM as a new part of this site is now online. Check it out!

MMSP21 Challenge: We host a challenge on structure-guided image inpainting. Take a look!

Friends

Useful Links

Windy: A website to provide visualized numerical weather forecast results by, e.g. GFS, ECMWF.

DLVC: An open-sourced deep-learning driven video codec.

FVC-NIC: Open-Source learned image compression framework.

BDWM: The most popular & official Bulletin Board System (BBS) at Peking University.

Selected Publications
  1. Yueyu Hu, Wenhan Yang, Zhan Ma, and Jiaying Liu. "Learning End-to-End Lossy Image Compression: A Benchmark", Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    [Project] [arXiv] [Early Access] [Code]
  2. Yueyu Hu, Wenhan Yang, and Jiaying Liu. "Coarse-to-Fine Hyper-Prior Modeling for Learned Image Compression", Proc. AAAI Conference on Artificial Intelligence (AAAI), 2020.
    [PDF] [Poster] [Project] [TF Code] [PyTorch Code] [Spotlight]
  3. Yueyu Hu, Wenhan Yang, Mading Li, and Jiaying Liu. "Progressive Spatial Recurrent Neural Network for Intra Prediction", IEEE Transactions on Multimedia (TMM), 2019.
    [PDF] [Code]
  4. Yueyu Hu, Shuai Yang, Wenhan Yang, Ling-Yu Duan, and Jiaying Liu. "Towards Coding for Human and Machine Vision: A Scalable Image Coding Approach", Proc. IEEE International Conference on Multimedia & Expo (ICME), 2020. (Best Paper Award)
    [PDF] [Project] [Slides]
  5. Shuai Yang, Yueyu Hu, Wenhan Yang, Ling-Yu Duan, and Jiaying Liu. "Towards Coding for Human and Machine Vision: Scalable Face Image Coding", IEEE Transactions on Multimedia (TMM), 2020.
    [PDF]
  6. Yueyu Hu, Chunhui Liu, Yanghao Li, Sijie Song and Jiaying Liu. "Temporal Perceptive Network for Skeleton-Based Action Recognition", Proc. British Machine Vision Conference (BMVC), 2017.
    [PDF]
  7. Haofeng Huang, Wenhan Yang, Yueyu Hu, and Jiaying Liu. "Raw-Guided Enhancing Reprocess of Low-Light Image via Deep Exposure Adjustment", Proc. Asian Conference on Computer Vision (ACCV), 2020.
    [PDF]
  8. [Full list of publications]

Projects

Towards Coding for Human and Machine Vision: A Scalable Image Coding Approach

In this paper, we come up with a novel image coding framework by leveraging both the compressive and the generative models, to support machine vision and human perception tasks jointly. By introducing advanced generative models, we train a flexible network to reconstruct images from compact feature representations and the reference pixels. Experimental results demonstrate the superiority of our framework in both human visual quality and facial landmark detection, which provide useful evidence on the emerging standardization efforts on MPEG VCM (Video Coding for Machine).

[PDF] [Supplementary] [Project]

Coarse-to-Fine Hyper-Prior Modeling for Learned Image Compression

End-to-End learned image compression framework with a coarse-to-fine hyper-prior model, featuring Signal Preserving Hyper Transform and Information Aggregation Reconstruction sub-network. The proposed model achieve superior performance to existing hyper-prior models with context models.

[PDF] [Poster] [Project] [Code] [Spotlight]

Learning End-to-End Lossy Image Compression: A Benchmark

A survey and benchmark of existing end-to-end learned image compression methods.

[arXiv] [Project]

Yueyu HU, 胡越予

Ph.D. Student, New York University

yyhu AT nyu·edu

About Me

I am currently pursuing a Ph.D. with Prof. Yao Wang at NYU Video Lab. I received a master's degree in computer science at Peking University, advised by Prof. Jiaying Liu at STRUCT. My research interests include computer vision, machine learning and image/video compression. I am also interested in photography, trains and railways, meteorology, science-fiction and computer network development.

WHIM as a new part of this site is now online. Check it out!

MMSP21 Challenge: We host a challenge on structure-guided image inpainting. Take a look!

Selected Publications
  1. Yueyu Hu, Wenhan Yang, Zhan Ma, and Jiaying Liu. "Learning End-to-End Lossy Image Compression: A Benchmark", Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    [Project] [arXiv] [Early Access] [Code]
  2. Yueyu Hu, Wenhan Yang, and Jiaying Liu. "Coarse-to-Fine Hyper-Prior Modeling for Learned Image Compression", Proc. AAAI Conference on Artificial Intelligence (AAAI), 2020.
    [PDF] [Poster] [Project] [Code] [Spotlight]
  3. Yueyu Hu, Wenhan Yang, Mading Li, and Jiaying Liu. "Progressive Spatial Recurrent Neural Network for Intra Prediction", IEEE Transactions on Multimedia (TMM), 2019.
    [PDF] [Code]
  4. Yueyu Hu, Shuai Yang, Wenhan Yang, Ling-Yu Duan, and Jiaying Liu. "Towards Coding for Human and Machine Vision: A Scalable Image Coding Approach", Proc. IEEE International Conference on Multimedia & Expo (ICME), 2020. (Best Paper Award)
    [PDF] [Project] [Slides]
  5. Shuai Yang, Yueyu Hu, Wenhan Yang, Ling-Yu Duan, and Jiaying Liu. "Towards Coding for Human and Machine Vision: Scalable Face Image Coding", IEEE Transactions on Multimedia (TMM), 2020.
    [PDF]
  6. Yueyu Hu, Chunhui Liu, Yanghao Li, Sijie Song and Jiaying Liu. "Temporal Perceptive Network for Skeleton-Based Action Recognition", Proc. British Machine Vision Conference (BMVC), 2017.
    [PDF]
  7. Haofeng Huang, Wenhan Yang, Yueyu Hu, and Jiaying Liu. "Raw-Guided Enhancing Reprocess of Low-Light Image via Deep Exposure Adjustment", Proc. Asian Conference on Computer Vision (ACCV), 2020.
    [PDF]
  8. [Full list of publications]

Projects

Towards Coding for Human and Machine Vision: A Scalable Image Coding Approach

In this paper, we come up with a novel image coding framework by leveraging both the compressive and the generative models, to support machine vision and human perception tasks jointly. By introducing advanced generative models, we train a flexible network to reconstruct images from compact feature representations and the reference pixels. Experimental results demonstrate the superiority of our framework in both human visual quality and facial landmark detection, which provide useful evidence on the emerging standardization efforts on MPEG VCM (Video Coding for Machine).

[PDF] [Supplementary] [Project]

Coarse-to-Fine Hyper-Prior Modeling for Learned Image Compression

End-to-End learned image compression framework with a coarse-to-fine hyper-prior model, featuring Signal Preserving Hyper Transform and Information Aggregation Reconstruction sub-network. The proposed model achieve superior performance to existing hyper-prior models with context models.

[PDF] [Poster] [Project] [TF Code] [PyTorch Code] [Spotlight]

Learning End-to-End Lossy Image Compression: A Benchmark

A survey and benchmark of existing end-to-end learned image compression methods.

[arXiv] [Project]

Friends


Useful Links

Windy: A website to provide visualized numerical weather forecast results by, e.g. GFS, ECMWF.

DLVC: An open-sourced deep-learning driven video codec.

FVC-NIC: Open-Source learned image compression framework.

BDWM: The most popular & official Bulletin Board System (BBS) at Peking University.