3 papers
cs.CV2026
DipGuava: Disentangling Personalized Gaussian Features for 3D Head Avatars from Monocular Video
Jeonghaeng Lee, Seok Keun Choi, Zhixuan Li +2
While recent 3D head avatar creation methods attempt to animate facial dynamics, they often fail to capture personalized details, limiting realism and expressiveness. To fill this…
cs.CV2025
Shape Distribution Matters: Shape-Specific Mixture-of-Experts for Amodal Segmentation Under Diverse Occlusions
Zhixuan Li, Yujia Liu, Chen Hui +3
Amodal segmentation aims to predict complete object masks covering both visible and occluded regions, serving as a critical foundation for robust multimedia scene understanding and…
cs.CV2025
Unveiling the Invisible: Reasoning Complex Occlusions Amodally with AURA
Zhixuan Li, Hyunse Yoon, Sanghoon Lee +1
Amodal segmentation aims to infer the complete shape of occluded objects, even when the occluded region's appearance is unavailable. However, current amodal segmentation methods la…