4 accepted papers
Generating realistic human motion videos is a pivotal challenge in advancing human-computer interaction. While existing approaches often focus on generating either head or gesture movements from audio, they lack unified control over full-body motion, frequently producing low-resolution and blurred o…
Pose-controlled human video generation is of significant interest and finds extensive applications in areas such as automated advertising and content creation on social media platforms. While existing methods employing pose sequences and reference images for human image animation have exhibited nota…
We propose VideoHumanMIB, a novel framework for Video Human Motion In-betweening that enables seamless transitions between different motion video clips, facilitating the generation of longer and more natural digital human videos. While existing video frame interpolation methods work well for similar
Audio-driven co-speech human gesture generation has made remarkable advancements recently. However, most previous works only focus on single person audio-driven gesture generation. We aim at solving the problem of conversational co-speech gesture generation that considers multiple participants in a…