CyberHost: Taming Audio-driven Avatar Diffusion Model with Region Codebook Attention
On the map: Diffusion models → Audio, speech and music
Abstract (arXiv)
Diffusion-based video generation technology has advanced significantly, catalyzing a proliferation of research in human animation. However, the majority of these studies are confined to same-modality driving settings, with cross-modality human body animation remaining relatively underexplored. In this paper, we introduce, an end-to-end audio-driven human animation framework that ensures hand integrity, identity consistency, and natural motion. The key design of CyberHost is the Region Codebook Attention mechanism, which improves the generation quality of facial and hand animations by integrating fine-grained local features with learned motion pattern priors. Furthermore, we have developed a suite of human-prior-guided training strategies, including body movement map, hand clarity score, pose-aligned reference feature, and local enhancement supervision, to improve synthesis results. To our knowledge, CyberHost is the first end-to-end audio-driven human diffusion model capable of facilitating zero-shot video generation within the scope of human body. Extensive experiments demonstrate that CyberHost surpasses previous works in both quantitative and qualitative aspects.
Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). Placed in Audio, speech and music, one of 14 directions in Diffusion models. Builds on 42 of its 55 references that are in the map. First posted on arXiv 3 Sep 2024.
Builds on
42 of 55 references.
Closest ancestors · 5
Same direction, newest first
- 2024Make-Your-Anchor: A Diffusion-based 2D Avatar Generation Framework25 Mar
- 2024VLOGGER: Multimodal Diffusion for Embodied Avatar Synthesis13 Mar
- 2024EMO: Emote Portrait Alive -- Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions27 Feb
- 2023Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generation16 Mar
- 2023Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation6 Jan
Other references · 37
- 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
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- 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,198
- 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
- 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,600
- 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,465
- 2023AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuningcited by 1,418
- 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animationcited by 683
- 2020A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wildcited by 669
- 2018DensePose: Dense Human Pose Estimation In The Wildcited by 573
- 2022MagicVideo: Efficient Video Generation With Latent Diffusion Modelscited by 463
- 2023VideoComposer: Compositional Video Synthesis with Motion Controllabilitycited by 461
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- 2020One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencingcited by 438
- 2024Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teacherscited by 389
- 2022Latent Video Diffusion Models for High-Fidelity Long Video Generationcited by 385
- 2022SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animationcited by 380
- 2023MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Modelcited by 330
- 2023Effective Whole-body Pose Estimation with Two-stages Distillationcited by 307
- 2021Motion Representations for Articulated Animationcited by 253
- 2022CelebV-HQ: A Large-Scale Video Facial Attributes Datasetcited by 246
- 2024Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image Animationcited by 198
- 2024MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidancecited by 196
- 2024EchoMimic: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditionscited by 196
- 2019Learning Individual Styles of Conversational Gesturecited by 190
- 2024VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Timecited by 186
- 2022StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGANcited by 169
- 2023DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusioncited by 167
- 2024Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesiscited by 153
- 2023TryOnDiffusion: A Tale of Two UNetscited by 141
- 2023DisCo: Disentangled Control for Realistic Human Dance Generationcited by 141
- 2024V-Express: Conditional Dropout for Progressive Training of Portrait Video Generationcited by 85
- 2023DR2: Diffusion-based Robust Degradation Remover for Blind Face Restorationcited by 79
- 2024EasyAnimate: High-Performance Video Generation Framework with Hybrid Windows Attention and Reward Backpropagationcited by 76
- 2021Speech Drives Templates: Co-Speech Gesture Synthesis with Learned Templatescited by 57
- 2022Audio-Driven Co-Speech Gesture Video Generationcited by 54
- 2023DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidancecited by 20
- 2024MobilePortrait: Real-Time One-Shot Neural Head Avatars on Mobile Devicescited by 12
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Citing papers per year: 2024: 5; 2025: 29; 2026: 4.
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