Loki replaces RGB conditioning stacks with identity-orthogonal parametric face encodings rasterized for diffusion, achieving efficient cross-ID portrait animation without cross-ID training data.
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AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait Animation
26 Pith papers cite this work. Polarity classification is still indexing.
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representative citing papers
A dual-path modulation technique injects independent emotion control into existing feed-forward single-image 3D head avatar pipelines while preserving reconstruction quality.
AvatarPointillist autoregressively generates adaptive 3D point clouds via Transformer for photorealistic 4D Gaussian avatars from one image, jointly predicting animation bindings and using a conditioned Gaussian decoder.
UIKA is a feed-forward animatable Gaussian head model using UV-guided correspondence estimation and learnable UV tokens with dual-level attention, trained on large-scale synthetic data to handle pose-free inputs.
ViBES introduces a speech-language-behavior model using modality-specific transformer experts that jointly generates dialogue and 3D body actions, showing gains over separate co-speech and text-to-motion baselines on multi-turn metrics.
Phoneme-guided autoregressive framework for talking-head animation that reduces inter-frame flicker via causal keyframe generation and timestamp-aware interpolation, outperforming diffusion baselines on FVD and a new BG-Flicker metric.
SyncCache accelerates DiT-based audio-driven portrait animation up to 4.12x via spatially-asymmetric probing and modality-decoupled caching while preserving near-lossless quality and audio sync.
A causal VAE with variable reference guidance and a Rectified Flow Transformer enables real-time streamable high-quality talking portrait video generation from audio and images.
Reformulates evaluation of audio-driven talking head generation as a sequence alignment problem using Soft DTW, showing improved robustness and consistency across 20 methods and seven datasets.
A fine-tuning-free framework combines pretrained Stable Diffusion with IP-Adapter plus three parameter-free modules to achieve improved lip synchronization and visual quality in talking face generation.
CogPortrait uses MLLM-based hierarchical planning to convert high-level labels into eye keypoints and a conditioned DiT model to produce portrait animations with improved eye-region accuracy on the new EMH benchmark.
TT-SAC is a parameter-free inference framework that uses a generator-encoder feedback loop to adapt conditioning representations and stabilize identity and motion in audio-driven talking-head videos.
AsymTalker uses temporal reference encoding and asymmetric knowledge distillation to produce identity-consistent talking head videos up to 600 seconds long at 66 FPS.
Translation function vectors extracted from a single English→X direction transfer across unseen target languages in three multilingual LLMs, extending language-agnosticity findings to task-level representations.
PianoFlow generates coordinated bimanual piano motions from audio via MIDI-distilled flow-matching, asymmetric role-gated interaction, and autoregressive streaming continuation, outperforming priors with 9x faster inference.
A multimodal adversarial attack using stage-sampled image nullification and cross-attention flattening degrades lip-sync and facial dynamics in Hallo-based talking-head generation.
JAM-Flow introduces a unified flow-matching model with a Multi-Modal Diffusion Transformer that jointly synthesizes facial motion and speech from text, audio, or motion inputs.
LetsTalk combines a multimodal diffusion transformer, noise-regularized memory bank, deep compression autoencoder, and symbiotic/direct fusion schemes to achieve state-of-the-art quality and efficiency in long-duration talking video generation.
Two-stage pipeline with region-aware attention and Mamba-enhanced diffusion achieves SOTA accuracy, naturalness and temporal coherence on audio-driven portrait animation benchmarks using a new 380-hour dataset.
Archon unifies seven modalities via modality-specific tokenizers and an autoregressive backbone pretrained on 72 tasks, plus a 4x-efficient video reparameterization and stepwise 'Thinking in Modality' procedure, and reports superior or comparable results on digital-human tasks.
Omni-Fake delivers a unified multimodal deepfake benchmark dataset and RL-driven detector that reports gains in accuracy, cross-modal generalization, and explainability over prior baselines.
PortraitDirector uses hierarchical disentanglement of spatial physical motions and semantic emotions to deliver controllable, high-fidelity real-time facial reenactment at 20 FPS.
TurboTalk uses progressive distillation from 4 steps to 1 step with distribution matching and adversarial training to achieve 120x faster single-step audio-driven talking avatar video generation.
JoyVASA decouples static 3D facial representations from identity-independent dynamic motion sequences generated by a diffusion transformer to produce audio-driven animations for humans and animals.
citing papers explorer
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Loki: Representation over Architecture for Diffusion-Based Portrait Animation
Loki replaces RGB conditioning stacks with identity-orthogonal parametric face encodings rasterized for diffusion, achieving efficient cross-ID portrait animation without cross-ID training data.
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Giving Faces Their Feelings Back: Explicit Emotion Control for Feedforward Single-Image 3D Head Avatars
A dual-path modulation technique injects independent emotion control into existing feed-forward single-image 3D head avatar pipelines while preserving reconstruction quality.
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AvatarPointillist: AutoRegressive 4D Gaussian Avatarization
AvatarPointillist autoregressively generates adaptive 3D point clouds via Transformer for photorealistic 4D Gaussian avatars from one image, jointly predicting animation bindings and using a conditioned Gaussian decoder.
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UIKA: Fast Universal Head Avatar from Pose-Free Images
UIKA is a feed-forward animatable Gaussian head model using UV-guided correspondence estimation and learnable UV tokens with dual-level attention, trained on large-scale synthetic data to handle pose-free inputs.
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ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body
ViBES introduces a speech-language-behavior model using modality-specific transformer experts that jointly generates dialogue and 3D body actions, showing gains over separate co-speech and text-to-motion baselines on multi-turn metrics.
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FluentAvatar: Flicker-Free Talking-Head Animation via Phoneme-Guided Autoregressive Modeling
Phoneme-guided autoregressive framework for talking-head animation that reduces inter-frame flicker via causal keyframe generation and timestamp-aware interpolation, outperforming diffusion baselines on FVD and a new BG-Flicker metric.
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SyncCache: Exploiting Asymmetric Dynamics for Fast Audio-Driven Portrait Animation
SyncCache accelerates DiT-based audio-driven portrait animation up to 4.12x via spatially-asymmetric probing and modality-decoupled caching while preserving near-lossless quality and audio sync.
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Real-Time Generation of Streamable Talking Portrait Video with Reference-Guided Deep Compression VAEs
A causal VAE with variable reference guidance and a Rectified Flow Transformer enables real-time streamable high-quality talking portrait video generation from audio and images.
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Temporally-Aligned Evaluation for Audio-Driven Talking Head Generation
Reformulates evaluation of audio-driven talking head generation as a sequence alignment problem using Soft DTW, showing improved robustness and consistency across 20 methods and seven datasets.
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IP-Adapter Is All You Need: Towards Fine-Tuning-Free Diffusion-Based Talking Face Generation
A fine-tuning-free framework combines pretrained Stable Diffusion with IP-Adapter plus three parameter-free modules to achieve improved lip synchronization and visual quality in talking face generation.
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CogPortrait: Fine-Grained Eye-Region Control in Portrait Animation via Hierarchical Agent Planning
CogPortrait uses MLLM-based hierarchical planning to convert high-level labels into eye keypoints and a conditioned DiT model to produce portrait animations with improved eye-region accuracy on the new EMH benchmark.
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Test-Time Self-Adaptive Conditioning for Stable Audio-Driven Talking-Head Generation
TT-SAC is a parameter-free inference framework that uses a generator-encoder feedback loop to adapt conditioning representations and stabilize identity and motion in audio-driven talking-head videos.
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AsymTalker: Identity-Consistent Long-Term Talking Head Generation via Asymmetric Distillation
AsymTalker uses temporal reference encoding and asymmetric knowledge distillation to produce identity-consistent talking head videos up to 600 seconds long at 66 FPS.
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MMControl: Unified Multi-Modal Control for Joint Audio-Video Generation
Translation function vectors extracted from a single English→X direction transfer across unseen target languages in three multilingual LLMs, extending language-agnosticity findings to task-level representations.
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PianoFlow: Music-Aware Streaming Piano Motion Generation with Bimanual Coordination
PianoFlow generates coordinated bimanual piano motions from audio via MIDI-distilled flow-matching, asymmetric role-gated interaction, and autoregressive streaming continuation, outperforming priors with 9x faster inference.
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SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation
A multimodal adversarial attack using stage-sampled image nullification and cross-attention flattening degrades lip-sync and facial dynamics in Hallo-based talking-head generation.
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JAM-Flow: Joint Audio-Motion Synthesis with Flow Matching
JAM-Flow introduces a unified flow-matching model with a Multi-Modal Diffusion Transformer that jointly synthesizes facial motion and speech from text, audio, or motion inputs.
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Multimodal Diffusion Transformer with Memory Bank for Scalable Long-Duration Talking Video Generation
LetsTalk combines a multimodal diffusion transformer, noise-regularized memory bank, deep compression autoencoder, and symbiotic/direct fusion schemes to achieve state-of-the-art quality and efficiency in long-duration talking video generation.
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Mamba-Enhanced Implicit Motion Learning for Audio-Driven Portrait Animation
Two-stage pipeline with region-aware attention and Mamba-enhanced diffusion achieves SOTA accuracy, naturalness and temporal coherence on audio-driven portrait animation benchmarks using a new 380-hour dataset.
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Archon: A Unified Multimodal Model for Holistic Digital Human Generation
Archon unifies seven modalities via modality-specific tokenizers and an autoregressive backbone pretrained on 72 tasks, plus a 4x-efficient video reparameterization and stepwise 'Thinking in Modality' procedure, and reports superior or comparable results on digital-human tasks.
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Omni-Fake: Benchmarking Unified Multimodal Social Media Deepfake Detection
Omni-Fake delivers a unified multimodal deepfake benchmark dataset and RL-driven detector that reports gains in accuracy, cross-modal generalization, and explainability over prior baselines.
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PortraitDirector: A Hierarchical Disentanglement Framework for Controllable and Real-time Facial Reenactment
PortraitDirector uses hierarchical disentanglement of spatial physical motions and semantic emotions to deliver controllable, high-fidelity real-time facial reenactment at 20 FPS.
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TurboTalk: Progressive Distillation for One-Step Audio-Driven Talking Avatar Generation
TurboTalk uses progressive distillation from 4 steps to 1 step with distribution matching and adversarial training to achieve 120x faster single-step audio-driven talking avatar video generation.
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JoyVASA: Portrait and Animal Image Animation with Diffusion-Based Audio-Driven Facial Dynamics and Head Motion Generation
JoyVASA decouples static 3D facial representations from identity-independent dynamic motion sequences generated by a diffusion transformer to produce audio-driven animations for humans and animals.
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EchoTorrent: Towards Swift, Sustained, and Streaming Multi-Modal Video Generation
EchoTorrent combines multi-teacher distillation, adaptive CFG calibration, hybrid long-tail forcing, and VAE decoder refinement to enable few-pass autoregressive streaming video generation with improved temporal consistency and audio-lip sync.
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Image-to-Video Diffusion: From Foundations to Open Frontiers
A survey that organizes diffusion image-to-video methods into a taxonomy, distills core designs in condition encoding, temporal modeling, noise prior, and upsampling, and discusses applications plus challenges.