Papers › High-quality Animatable Eyelid Shapes from Lightweight Captures
High-quality Animatable Eyelid Shapes from Lightweight Captures
Junfeng Lyu, Feng Xu
High-quality eyelid reconstruction and animation are challenging for the subtle details and complicated deformations. Previous works usually suffer from the trade-off between the capture costs and the quality of details. In this paper, we propose a novel method that can achieve detailed eyelid reconstruction and animation by only using an RGB video captured by a mobile phone. Our method utilizes both static and dynamic information of eyeballs (e.g., positions and rotations) to assist the eyelid reconstruction, cooperating with an automatic eyeball calibration method to get the required eyeball parameters. Furthermore, we develop a neural eyelid control module to achieve the semantic animation control of eyelids. To the best of our knowledge, we present the first method for high-quality eyelid reconstruction and animation from lightweight captures. Extensive experiments on both synthetic and real data show that our method can provide more detailed and realistic results compared with previous methods based on the same-level capture setups. The code is available at https://github.com/StoryMY/AniEyelid.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections