|
Xuanbai Chen is an Applied Scientist in AWS AI Rekognition team, and is currently working on face recognition and trustworthy AI. Prior to AWS, he obtained my Master of Science in Computer Vision (MSCV) Degree in the Robotics Institute, School of Computer Science, Carnegie Mellon University. He worked with Prof. Fernando De la Torre on Fairness for Generation Model and 3D Face modeling. He obtained my Bachelor of Engineering in Computer Science (B.Eng in CS) Degree in College of Computer Science, Nankai University, working on Video Summarization. Email / LinkedIn / Google Scholar / CV |
|
|
|
|
|
|
Video Summarization via Knowledge-Aware Multimodal Deep Networks
Jiehang Xie, Xuanbai Chen, Sicheng Zhao, Shao-Ping Lu KBS, 2024 project page Propose a novel video summarization approach based on a knowledge-aware multimodal network. |
|
Towards Effective Usage of Human-Centric Priors in Diffusion Models for Text-based Human Image Generation
Junyan Wang, Zhenhong Sun, Zhiyu Tan, Xuanbai Chen, Weihua Chen, Hao Li, Cheng Zhang, Yang Song CVPR, 2024 project page / arXiv / code Integrating human-centric priors to help t2i model better generate human images. |
|
ITI-GEN: Inclusive Text-to-Image Generation
Cheng Zhang, Xuanbai Chen, Siqi Chai, Chen Henry Wu, Dmitry Lagun, Thabo Beeler, Fernando De la Torre ICCV, 2023 (Oral Presentation, Best Paper Finalist, 17 out of 8260 submissions) project page / arXiv / code / data / poster Debias the text-to-image generation model and implement the inclusiveness. |
|
Controllable 3D Generative Adversarial Face Model via Disentangling Shape and Appearance
Fariborz Taherkhani, Aashish Rai, Quankai Gao, Shaunak Srivastava, Xuanbai Chen, Fernando De la Torre, Steven Song, Aayush Prakash, Daeil Kim WACV, 2023 project page / arXiv / code / video A new 3D face generative model that can decouple identity and expression and provides granular control over expressions. |
|
A Knowledge Augmented and Multimodal-Based Framework for Video Summarization
Jiehang Xie*, Xuanbai Chen*, Shao-Ping Lu, Yulu Yang ACMMM, 2022 project page / video Propose a knowledge augmented and multimodal-based video summarization method, by considering multichannel information and using the impact of external knowledge. |
|
Multimodal-based and Aesthetic-guided Narrative Video Summarization
Jiehang Xie, Xuanbai Chen, Tianyi Zhang, Yixuan Zhang, Shao-Ping Lu, Pablo Cesar, Yulu Yang IEEE TMM, 2022 project page Introduce a multimodal-based and aesthetic-guided narrative video summarization method, by leveraging multimodal information through specified key shots selection, subtitle summarization, and highlight extraction components. |
|
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation
Sicheng Zhao*, Xuanbai Chen*, Xiangyu Yue, Chuang Lin, Pengfei Xu, Ravi Krishna, Jufeng Yang, Ding Guiguang, Alberto Sangiovanni Vincentelli, Kurt Keutzer IEEE TCYB, 2021 project page / arxiv Design a novel end-to-end cycle-consistent adversarial model, to focus on UDA in visual emotion analysis for both emotion distribution learning and dominant emotion classification. |
|
|
|
AWS AI Rekognition, Jul. 2023 - Present Applied Scientist |
|
Carnegie Mellon University, Jan. 2022 - May. 2023 Master of Science in Computer Vision |
|
|
AWS AI Rekognition, May. 2022 - Aug. 2022 Applied Scientist Intern |
|
Sensetime, Aug. 2021 - Dec. 2021 Research Engineer Intern |
|
University of California, Berkeley, Jan. 2020 - May. 2020 Exchange Program |
|
Nankai University, Sep. 2017 - Jun. 2021 Bachelor of Engineering in Computer Science |
|
|
|
The initial label for me is a sports fan and I love watching various sports games in my leisure time. My favorite players are LeBron James, Lionel Messi, Roger Federer for basketball, football, and tennis respectively. Furthermore, I will also spend some time in watching popularization videos in different subjects to prevent me from being 'ignorant' in other fields. |