Pith. sign in

REVIEW 11 cited by

Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2401.08503 v3 pith:CJZDZEKU submitted 2024-01-16 cs.CV

Zhenhui Ye , Tianyun Zhong , Yi Ren , Jiaqi Yang , Weichuang Li , Jiawei Huang , Ziyue Jiang , Jinzheng He
show 6 more authors
Rongjie Huang Jinglin Liu Chen Zhang Xiang Yin Zejun Ma Zhou Zhao
This is my paper · ORCID
classification cs.CV
keywords talkingportraitvideomodelone-shotrealisticfaceaccurate
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

One-shot 3D talking portrait generation aims to reconstruct a 3D avatar from an unseen image, and then animate it with a reference video or audio to generate a talking portrait video. The existing methods fail to simultaneously achieve the goals of accurate 3D avatar reconstruction and stable talking face animation. Besides, while the existing works mainly focus on synthesizing the head part, it is also vital to generate natural torso and background segments to obtain a realistic talking portrait video. To address these limitations, we present Real3D-Potrait, a framework that (1) improves the one-shot 3D reconstruction power with a large image-to-plane model that distills 3D prior knowledge from a 3D face generative model; (2) facilitates accurate motion-conditioned animation with an efficient motion adapter; (3) synthesizes realistic video with natural torso movement and switchable background using a head-torso-background super-resolution model; and (4) supports one-shot audio-driven talking face generation with a generalizable audio-to-motion model. Extensive experiments show that Real3D-Portrait generalizes well to unseen identities and generates more realistic talking portrait videos compared to previous methods. Video samples and source code are available at https://real3dportrait.github.io .

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 11 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Instant Expressive Gaussian Head Avatars at Over 100 FPS

    cs.CV 2025-12 conditional novelty 7.0 of 10

    A single-photo avatar encoder with per-Gaussian feature-space deformation animates faces at 107 FPS with expression quality competitive with diffusion models.

  2. FantasyPortrait: Enhancing Multi-Character Portrait Animation with Expression-Augmented Diffusion Transformers

    cs.CV 2025-07 conditional novelty 7.0 of 10

    A DiT-based portrait animation model transfers implicit facial expressions to one or more characters using a masked cross-attention mechanism, supported by a new multi-face dataset and benchmark.

  3. FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images

    cs.CV 2026-06 unverdicted novelty 6.0 of 10

    FFAvatar uses a Transformer-based 3D Gaussian model with alternating attention and sparse-to-dense learning to enable feed-forward, incremental reconstruction of animatable 4D head avatars from sparse portrait images.

  4. Mask-Free Audio-driven Talking Face Generation for Enhanced Visual Quality and Identity Preservation

    cs.CV 2025-07 conditional novelty 6.0 of 10

    MF-Talk, a mask-free and identity-reference-free three-stage pipeline, improves visual quality and identity preservation in talking-face generation while remaining competitive on lip-sync.

  5. JOLT3D: Joint Learning of Talking Heads and 3DMM Parameters with Application to Lip-Sync

    cs.CV 2025-07 conditional novelty 6.0 of 10

    JOLT3D jointly trains a 3DMM reconstruction network with a talking head generator, then uses FACS mouth blendshapes from a diffusion model to lip-sync videos while preserving the original chin contour.

  6. Total-Editing: Head Avatar with Editable Appearance, Motion, and Lighting

    cs.CV 2025-05 conditional novelty 6.0 of 10

    Total-Editing is a unified 3D head avatar framework that separately controls appearance, motion, and lighting through an intrinsically decomposed neural radiance field, and reports stronger identity, expression, pose,...

  7. Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model

    cs.CV 2025-02 conditional novelty 6.0 of 10

    A motion-prior diffusion model with archived-frame memory improves identity, lip-sync, and head-motion consistency in long talking-face videos.

  8. FA-LAM: Focus-Aware Large Avatar Model for One-Shot 4D Animatable Gaussian Head

    cs.CV 2026-07 conditional novelty 5.0 of 10

    A one-shot model for animatable 3D/4D Gaussian head reconstruction that adds attention regularization, decoupled reconstruction-animation training, and autoregressive visibility-gated fusion, reporting consistent metr...

  9. GGTalker: Talking Head Systhesis with Generalizable Gaussian Priors and Identity-Specific Adaptation

    cs.CV 2025-06 conditional novelty 5.0 of 10

    GGTalker combines large-scale audio-to-expression and expression-to-texture priors with rapid per-identity fine-tuning to create high-quality 3D talking heads from a short video.

  10. SkyReels-Audio: Omni Audio-Conditioned Talking Portraits in Video Diffusion Transformers

    cs.CV 2025-06 conditional novelty 5.0 of 10

    An audio-conditioned video diffusion transformer that animates portraits from image, video, text, and audio inputs with a sliding-window fusion for long videos.

  11. Livatar-1: Real-Time Talking Heads Generation with Tailored Flow Matching

    cs.CV 2025-07 reject novelty 4.0 of 10

    Livatar claims the best lip-sync score in its comparison table and real-time throughput, but the preprint does not describe the model or release any code, data, or weights.

Pith tools