Conditional motion in-betweening

•We propose a conditional motion in-betweening (CMIB) method, providing additional controllability in motion in-betweening (MIB). The proposed method can perform two different CMIB tasks, pose-conditioned and semantic-conditioned MIB.•We propose a motion data augmentation method, which is effective in pose-conditioned MIB tasks by defining a probability distribution over smooth trajectories.•Our proposed method achieves state-of-the-art performance on MIB tasks on multiple motion capture databases while providing additional controllability.•We present an evaluation measure for semantic-conditioned MIB tasks.