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Found 4 papers, 2 papers with code
MoConVQ: Unified Physics-Based Motion Control via Scalable Discrete Representations
In this work, we present MoConVQ, a novel unified framework for physics-based motion control leveraging scalable discrete representations.
Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data
How to automatically synthesize natural-looking dance movements based on a piece of music is an incrementally popular yet challenging task.
GestureDiffuCLIP: Gesture Diffusion Model with CLIP Latents
We leverage the power of the large-scale Contrastive-Language-Image-Pre-training (CLIP) model and present a novel CLIP-guided mechanism that extracts efficient style representations from multiple input modalities, such as a piece of text, an example motion clip, or a video.
Rhythmic Gesticulator: Rhythm-Aware Co-Speech Gesture Synthesis with Hierarchical Neural Embeddings
We present a novel co-speech gesture synthesis method that achieves convincing results both on the rhythm and semantics.
Ranked #2 on
Gesture Generation
on TED Gesture Dataset
