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Found 7 papers, 5 papers with code
Co-Speech Gesture Video Generation via Motion-Decoupled Diffusion Model
While previous works mostly generate structural human skeletons, resulting in the omission of appearance information, we focus on the direct generation of audio-driven co-speech gesture videos in this work.
Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning
Leveraging unseen LR images for self-supervised learning guides the model to adapt its modeling space to the target domain, facilitating fine-tuning of SR models without requiring paired high-resolution (HR) images.
Semantics-aware Motion Retargeting with Vision-Language Models
Capturing and preserving motion semantics is essential to motion retargeting between animation characters.
UnifiedGesture: A Unified Gesture Synthesis Model for Multiple Skeletons
The automatic co-speech gesture generation draws much attention in computer animation.
The DiffuseStyleGesture+ entry to the GENEA Challenge 2023
In this paper, we introduce the DiffuseStyleGesture+, our solution for the Generation and Evaluation of Non-verbal Behavior for Embodied Agents (GENEA) Challenge 2023, which aims to foster the development of realistic, automated systems for generating conversational gestures.
QPGesture: Quantization-Based and Phase-Guided Motion Matching for Natural Speech-Driven Gesture Generation
Levenshtein distance based on audio quantization as a similarity metric of corresponding speech of gestures helps match more appropriate gestures with speech, and solves the alignment problem of speech and gestures well.
CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimation
Top-down methods dominate the field of 3D human pose and shape estimation, because they are decoupled from human detection and allow researchers to focus on the core problem.
Ranked #1 on
Unsupervised 3D Human Pose Estimation
on Human3.6M
(PA-MPJPE metric)
