On AI Lounge since Oct 2026
Fating Hong
Member #669DeveloperL3PhD Student, Hong Kong University of Science and Technology (HKUST)
GAN, Talking Head Generation, Video Understanding
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Achievements
Plugged In ×4Connected sources: GitHub, Hugging Face, LinkedIn, X, website.How: Connected 4 sources (GitHub, LinkedIn, X or a website) in Settings
Plugged In×4Featured
Shipper ×2Projects on your profile.How: Added 5 projects to their profile
Shipper×2
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Pinned projects
The official code of our ICCV2023 work: Implicit Identity Representation Conditioned Memory Compensation Network for Talking Head video Generation
animationdeepfakefaceganimage-generationmotion-transfer
Video Evaluation, PSNR, SSM, LPIPS, VBENCH
Official code for CVPR2022 paper: Depth-Aware Generative Adversarial Network for Talking Head Video Generation
deepfakedepthfaceface-reenactmentganimage-animation
face-reenactmentimage-animationmotion-transfertalking-head
A curated list of papers, datasets and benchmarks for text-driven 3D human motion editing, grouped by the supervision each method assumes.
3d-human-motionawesomeawesome-listbenchmarkcomputer-graphicscomputer-vision
About
Fating Hong is a computer science researcher from Hong Kong University of Science and Technology (HKUST), where he was advised by Prof. Dan Xu. He works on talking head generation, avatar animation and video generation. Fating is the author of the CVPR 2022 DaGAN, ICCV 2023 MCNET and ICCV 2025 ACTalker papers, and he earlier did master's research in video understanding at Sun Yat-sen University.
Categories
Experience
ND
Research Intern · nternational Digital Economy Academy
Research Intern · Tencent
Education
The Hong Kong University of Science and Technology (HKUST)
Sun Yat-sen University
