COIN: Control-Inpainting Diffusion Prior for Human and Camera Motion
Estimation
COIN: Control-Inpainting Diffusion Prior for Human and Camera Motion
Estimation
Estimating global human motion from moving cameras is challenging due to the entanglement of human and camera motions. To mitigate the ambiguity, existing methods leverage learned human motion priors, which however often result in oversmoothed motions with misaligned 2D projections. To tackle this problem, we propose COIN, a control-inpainting motion …