SignMimic: Robust High-Quality Sign Language Motion Generation via Human-Shape-Oblivious Pose Transfer Guidance

arXiv:2609.14122 · cs.CV · Submitted 2026-09-12 · Read on arXiv

cs.CV

Submitted: 2026-09-12

Updated: 2026-09-24

Code: https://github.com/deepinsight/insightface

Terminology

• Consistency — 12× in this paper · explained in 3 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Diffusion Model — 9× in this paper · explained in 8 episodes
• Transformer — 9× in this paper · explained in 2 episodes
• Diffusion Models — 8× in this paper · explained in 6 episodes
• Adaptation — 7× in this paper · explained in 1 episode
• Fidelity — 6× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Sign Language Translation — 4× in this paper
• Temporal consistency — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Representation Learning — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Stable Video Diffusion — 2× in this paper
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Alignment Problem — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Entanglement — 1× in this paper · explained in 4 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Optical Flow — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• Using THELI pipeline in order to reduce Abell 226 multi-band optical images
• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)
• Deep High-Resolution Representation Learning for Human Pose Estimation
• Towards Accurate Generative Models of Video: A New Metric & Challenges
• SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition
• Effective Whole-body Pose Estimation with Two-stages Distillation
• RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
• Swapping of quantum correlations and the role of local filtering operations
• MediaPipe: A Framework for Building Perception Pipelines

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