'Jing Chen PhD' - A Research Journey in Machine Learning, Computer Vision, and Graphics

Jing Liao, a third-year PhD candidate under the supervision of 'co-supervisor names', has been making significant contributions to the field of machine learning, computer vision, and graphics. His research interests span across multiple areas, including neural implicit fields, diffusion models, facial action unit recognition, face manipulation, and 3D scene generation.

In his recent publications, Jing Liao has demonstrated expertise in leveraging generative adversarial networks (GANs) for personalized multiple facial action unit recognition ('1'). He has also explored the use of dual learning for joint facial landmark detection and action unit recognition ('2').

Another notable achievement is his work on cross-domain and disentangled face manipulation with 3D guidance, which was presented at the EGSR & CGF conference in 2021. This research showcased his ability to manipulate faces while maintaining their original characteristics.

Jing Liao's recent publications have also focused on neural radiance fields, including CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields ('3'), FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editing ('4'), and NeRF-Art: Text-Driven Neural Radiance Fields Stylization ('5'). These papers demonstrate his expertise in manipulating neural radiance fields using text-based input.

Additionally, Jing Liao has explored the use of diffusion models for 3D scene generation with Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields ('6').

Jing Liao's research journey began as a research intern at Meta Reality Lab, Codec Avatar team, where he worked alongside Menglei Chai, Mingming He, and Dongdong Chen. As a PhD candidate, he is currently focusing on neural implicit fields and diffusion models.

For those interested in learning more about Jing Liao's research, please feel free to reach out via email at 'email address'.

References:

'1' Jing Chen et al., 'Personalized Multiple Facial Action Unit Recognition through Generative Adversarial Recognition Network,' IEEE Transactions on Affective Computing, 2021.

'2' Jing Chen et al., 'Dual Learning for Joint Facial Landmark Detection and Action Unit Recognition,' IEEE Transactions on Visualization and Computer Graphics, 2021.

'3' I. Wang et al., 'CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields,' CVPR, 2022.

'4' J. Liao et al., 'FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editing,' SIGGRAPH Asia, 2022.

'5' I. Wang et al., 'NeRF-Art: Text-Driven Neural Radiance Fields Stylization,' ICCV, 2023.

'6' J. Liao et al., 'Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields,' (Under review).

Jing chen phd