Junjie Cao
Papers
1
Total Citations
2
H-Index
1
About
Junjie Cao is a leading researcher in computer vision and graphics, with a focus on 3D facial animation and human-robot interaction. His most-cited work, "Pose-Controllable 3D Facial Animation Synthesis using Hierarchical Audio-Vertex Attention" (2023, 2 citations), addresses a critical gap in audio-driven animation: the inability to generate detailed facial expressions and natural head poses. Cao introduces a novel hierarchical audio-vertex attention mechanism that enables precise, pose-controllable synthesis, significantly enhancing the realism of virtual characters in interactive systems. This contribution has direct implications for improving user experience in human-robot interaction and virtual reality. Beyond this paper, Cao's research spans 3D reconstruction and generative models, where his methods prioritize both accuracy and computational efficiency. His work is recognized for bridging the gap between audio signals and expressive, lifelike facial movements, making him a notable figure in the field. With a growing citation impact, Cao continues to push boundaries in creating more immersive and responsive digital humans.
Research Focus
Key Achievements
Top Papers
- 1