Hyeonho Jeong

Hyeonho Jeong

AI Researcher @ Adobe Research

About Me

I am a researcher at Adobe working on video generation and editing. Currently, I am primarily focused on bringing long video generation and editing capabilities to Video Firefly. I have additionally worked on camera-controllable video generation for Firefly foundational models. Previously at KAIST AI, I worked on improving the controllability and efficiency of video synthesis using diffusion models under the supervision of Prof. Jong Chul Ye.

Adobe Research Internship / University Collaboration: If you are interested in collaborating with me, don't hesitate to reach out via my work email.
Adobe internships are usually discussed around November, December of the year preceding it.

News

Publications

  1. Memory-V2V
    Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing
    Dohun Lee, Chun-Hao Paul Huang, Xuelin Chen, Jong Chul Ye, Duygu Ceylan, Hyeonho Jeong
    arXiv, 2026
    arXiv Project
  2. TrajectoryMover
    TrajectoryMover: Generative Movement of Object Trajectories in Videos
    Kiran Chhatre, Hyeonho Jeong, Yulia Gryaditskaya, Christopher E. Peters, Chun-Hao Paul Huang, Paul Guerrero
    arXiv, 2026
    arXiv Project
  3. SpaceTimePilot CVPR
    SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and Time
    Zhening Huang, Hyeonho Jeong, Xuelin Chen, Yulia Gryaditskaya, Tuanfeng Y. Wang, Joan Lasenby, Chun-Hao Huang
    IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2026
    arXiv Project
  4. Reangle-A-Video ICCV
    Reangle-A-Video: 4D Video Generation as Video-to-Video Translation
    Hyeonho Jeong*, Suhyeon Lee*, Jong Chul Ye
    International Conference on Computer Vision (ICCV), 2025
    arXiv Project
  5. JOG3R BMVC
    On Unifying Video Generation and Camera Pose Estimation
    Chun-Hao P. Huang, Niloy J. Mitra, Hyeonho Jeong, Jae Shin Yoon, Duygu Ceylan
    The 36th British Machine Vision Conference (BMVC), 2025
    arXiv Project
  6. Track4Gen CVPR
    Track4Gen: Teaching Video Diffusion Models to Track Points Improves Video Generation
    Hyeonho Jeong, Chun-Hao P. Huang, Jong Chul Ye, Niloy J. Mitra, Duygu Ceylan
    IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2025
    arXiv Project
  7. SMA AAAI
    Spectral Motion Alignment for Video Motion Transfer using Diffusion Models
    Geon Yeong Park*, Hyeonho Jeong*, Sang Wan Lee, Jong Chul Ye
    The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025
    arXiv Project Code
  8. DreamMotion ECCV
    DreamMotion: Space-Time Self-Similar Score Distillation for Zero-Shot Video Editing
    Hyeonho Jeong, Jinho Chang, Geon Yeong Park, Jong Chul Ye
    The 18th European Conference on Computer Vision (ECCV), 2024
    arXiv Project
  9. VMC CVPR
    VMC: Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models
    Hyeonho Jeong*, Geon Yeong Park*, Jong Chul Ye
    IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024
    arXiv Project Code Data
  10. Ground-A-Video ICLR
    Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models
    Hyeonho Jeong, Jong Chul Ye
    International Conference on Learning Representations (ICLR), 2024
    arXiv Project Code
  11. LAMP ICASSP
    Neural Network Training Strategy to Enhance Anomaly Detection Performance
    YeongHyeon Park, Sungho Kang, Myung Jin Kim, Hyeonho Jeong, Hyunkyu Park, Hyeong Seok Kim, Juneho Yi
    International Conference on Acoustics, Speech, & Signal Processing (ICASSP), 2024
    arXiv

Past Interns

I was lucky enough to have worked with the wonderful talents: