InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds

Figure 1 . InstantAvatar: we propose a system that can reconstruct animatable high-fidelity human avatars from a monocular video within 60 seconds, providing poses and masks, and can animate and render the model at 15 FPS at 540 × 540 resolution. To achieve this we integrate accelerated neural radiance fields, originally designed for rigid scenes, with a fast correspondence search module for articulation. An efficient empty-space skipping strategy further speeds up training and inference, enabling near-instant avatar learning.