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MagicInfinite: Generating Infinite Talking Videos with Your Words and Voice

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arxiv 2503.05978 v1 pith:6AISZAKX submitted 2025-03-07 cs.CV

classification cs.CV
keywords magicinfiniteacrossdiverseaudiocharactercharacterscontrolenabling
verification ladder T0 review T1 audit T2 compute T3 formal
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We present MagicInfinite, a novel diffusion Transformer (DiT) framework that overcomes traditional portrait animation limitations, delivering high-fidelity results across diverse character types-realistic humans, full-body figures, and stylized anime characters. It supports varied facial poses, including back-facing views, and animates single or multiple characters with input masks for precise speaker designation in multi-character scenes. Our approach tackles key challenges with three innovations: (1) 3D full-attention mechanisms with a sliding window denoising strategy, enabling infinite video generation with temporal coherence and visual quality across diverse character styles; (2) a two-stage curriculum learning scheme, integrating audio for lip sync, text for expressive dynamics, and reference images for identity preservation, enabling flexible multi-modal control over long sequences; and (3) region-specific masks with adaptive loss functions to balance global textual control and local audio guidance, supporting speaker-specific animations. Efficiency is enhanced via our innovative unified step and cfg distillation techniques, achieving a 20x inference speed boost over the basemodel: generating a 10 second 540x540p video in 10 seconds or 720x720p in 30 seconds on 8 H100 GPUs, without quality loss. Evaluations on our new benchmark demonstrate MagicInfinite's superiority in audio-lip synchronization, identity preservation, and motion naturalness across diverse scenarios. It is publicly available at https://www.hedra.com/, with examples at https://magicinfinite.github.io/.

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Forward citations

Cited by 6 Pith papers

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

  1. OmniCustom: Sync Audio-Video Customization Via Joint Audio-Video Generation Model

    cs.SD 2026-02 conditional novelty 6.0 of 10

    A zero-shot model that generates a video of a reference face speaking user-chosen text with a reference voice timbre.

  2. Avatar Forcing: Real-Time Interactive Head Avatar Generation for Natural Conversation

    cs.LG 2026-01 conditional novelty 6.0 of 10

    A causal diffusion-forcing model generates interactive head-avatar motion with 500ms motion-generation latency and learns expressive reactions via DPO with synthetic negative samples.

  3. AlignHuman: Improving Motion and Fidelity via Timestep-Segment Preference Optimization for Audio-Driven Human Animation

    cs.CV 2025-06 conditional novelty 5.0 of 10

    Timestep-segment preference optimization with separate motion and fidelity LoRAs improves audio-driven human animation quality and allows a 3.3x inference speedup.

  4. Seeing Voices: Generating A-Roll Video from Audio with Mirage

    cs.CV 2025-06 reject novelty 5.0 of 10

    Mirage generates photorealistic A-roll videos of people speaking directly from audio, using only joint self-attention over audio, text, and video tokens.

  5. TalkingMachines: Real-Time Audio-Driven FaceTime-Style Video via Autoregressive Diffusion Models

    cs.SD 2025-06 conditional novelty 5.0 of 10

    A pretrained 14B image-to-video diffusion model is adapted into a two-step autoregressive audio-driven avatar generator that can stream indefinitely in real time.

  6. 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.

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