Hao Tang
Computer Vision Lab, ETH Zürich, Switzerland
Office: ETF C 108, Sternwartstrasse 7, 8092 Zürich, Switzerland🇨🇭
Email: hao.tang@vision.ee.ethz.ch
Hey, thanks for stopping by! 👋
I am currently a postdoctoral researcher with Computer Vision Lab, ETH Zürich, Switzerland🇨🇭. I received my master’s degree from the School of Electronics and Computer Engineering, Peking University, China🇨🇳, and my Ph.D. degree from the Multimedia and Human Understanding Group, University of Trento, Italy🇮🇹. I was a visiting scholar in the Department of Engineering Science at the University of Oxford, UK🇬🇧, and in the Department of Computer Science at the Texas State University, USA🇺🇸.
My research interests are deep learning, machine learning, and their applications to computer vision. Specifically, I focus on:
- GANs (e.g., image generation, image translation, text-to-image synthesis/editing, person image synthesis, semantic image synthesis, style transfer, video generation)
- Diffusion models
- Low-level vision (image/video restoration, super-resolution, denoising, deblurring)
- Multi-modalities (e.g., audio-to-video synthesis, language-vision models)
- Medical image enhancement and analysis
- 3D vision (e.g., nerf, 3D-aware image/video generation, object reconstruction/generation, 3D pose transfer)
- Human pose estimation and motion prediction
- Depth estimation
- Semantic segmentation
- Object detection
- Efficient networks
- Network robustness
If this resonates with you, we are actively hiring. For prospective collaborators, we have multiple positions for Postdoc/Ph.D./Master/Intern researchers. If you are interested in joining/visitng ETH Computer Vision Lab or remotely working with us, please email me with your self-introduction, the project of interest (what is the problem you are trying to solve? and how are you trying to solve this problem (be as specific as possible)?), and CV to hao.tang@vision.ee.ethz.ch.
For ETH undergraduate and master students and students in the European area, please refer to this page (Connecting 3D and 2D, Deep Learning for Motion Prediction and Generation, Deep Learning for Space Design Generation, GANs Meet Nerfs, Deep Learning for Virtual Try-On, Deep Learning for Video Generation) and this page (Diffusion Models for Vision Tasks) for our MA/SA projects.
News
| 2023-01 | We have 1 paper accepted to ICLR 2023 and 1 paper accepted to TMM. |
|---|---|
| 2022-11 | We have 4 papers accepted to AAAI 2023, 1 paper accepted to IJCV, 1 paper accepted to TIP, and 1 paper accepted to TCSVT. |
| 2022-10 | We have 1 paper accepted to BMVC 2022 and 1 paper accepted to TPAMI. |
| 2022-09 | We have 1 paper accepted to TAFFC and 1 paper accepted to TGRS. |
| 2022-07 | We have 5 papers accepted to ECCV 2022, 1 paper accepted to TIP, and 1 paper accepted to PR. |
| 2022-06 | We have 2 papers accepted to ACM MM 2022. |
| 2022-04 | We have 1 paper accepted to IJCAI 2022, 1 paper accepted to TGRS, and 1 paper accepted to TMM. |
| 2022-03 | We have 5 papers accepted to CVPR 2022, 1 paper accepted to TPAMI, and 1 paper accepted to TMM. |
| 2021-12 | We have 2 papers accepted to AAAI 2022. |
| 2021-11 | We have 1 paper accepted to TIP. |
| 2021-10 | We have 3 papers accepted to BMVC 2021. |
| 2021-08 | We have 1 paper accepted to TIP and 1 paper accepted to TNNLS. |
| 2021-07 | We have 2 papers accepted to ICCV 2021. |
| 2021-06 | We have 1 paper accepted to ACM MM 2021 and 1 paper accepted to TMM. |
| 2020-08 | We have 1 paper accepted to BMVC 2020, 2 papers accepted to ACM MM 2020, and 1 paper accepted to TIP. |
| 2020-07 | We have 1 paper accepted to ECCV 2020. |
| 2020-05 | We have 1 paper accepted to TNNLS and 1 paper accepted to TGRS. |
| 2020-02 | We have 1 paper accepted to CVPR 2020. |
| 2019-07 | We have 1 paper accepted to ACM MM 2019. |
| 2019-02 | We have 1 paper accepted to CVPR 2019. |
| 2018-06 | We have 1 paper accepted to ACM MM 2018. |
| 2018-02 | We have 1 paper accepted to CVPR 2018. |
| 2016-07 | We have 1 paper accepted to IJCAI 2016. |
| 2015-08 | We have 1 paper accepted to ACM MM 2015. |