Chehre introduces a new emoji-prompted video dataset with multi-annotator labels to benchmark models on dominant and distributional facial expression recognition tasks.
hub Mixed citations
Liveportrait: Efficient portrait animation with stitching and retargeting control
Mixed citation behavior. Most common role is background (60%).
27
Pith papers citing it
Background
60% of classified citations
hub tools
citation-role summary
background 3
dataset 1
method 1
citation-polarity summary
representative citing papers
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.
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.
Omni-Attribute is a new open-vocabulary image attribute encoder trained on semantically linked pairs with dual objectives to produce disentangled representations for personalization and compositional generation.
A pose-conditioned large-margin contrastive encoder isolates persistent biometric identity cues from transmitted latents in talking-head videoconferencing to flag impersonation attacks via cosine similarity without inspecting the output video.
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.
Durian introduces a dual-reference diffusion model trained via self-reconstruction on video frames to enable cross-identity attribute transfer in portrait animations, supporting multi-attribute composition and interpolation.
InterTalk generates real-time multi-participant conversational talking-face videos by iteratively refining each person's lip, eye, and head motions from other participants' audio and motion feedback.
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.
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.
TOPOS creates high-fidelity 3D heads with fixed industry topology from single images via a specialized VAE with Perceiver Resampler and a rectified flow transformer.
Deepfake detectors act as alpha blending searchers; training solely on self-blended real images yields top cross-dataset generalization on 15 datasets without using synthetic deepfakes.
SocialDirector uses spatiotemporal actor masking and directional reweighting on cross-attention maps to reduce actor-action mismatches and improve target-directed interactions in generated multi-person videos.
MeshLAM reconstructs high-fidelity animatable textured mesh head avatars from a single image via a feed-forward dual shape-texture architecture with iterative GRU decoding and reprojection-based guidance.
ARGen uses AU-guided prompts and a reinforcement-learned diffusion strategy to synthesize scarce-class facial expression videos that improve dynamic emotion recognition.
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.
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.
SteerFace perturbs identity embeddings toward random orthogonal directions on the hypersphere with an adaptive strategy to mitigate visual tendency in synthetic faces and improve downstream recognition performance.
EasyVFX decouples VFX generation via frequency-aware Mixture-of-Experts and test-time training to achieve realistic effects with limited resources.
PortraitDirector uses hierarchical disentanglement of spatial physical motions and semantic emotions to deliver controllable, high-fidelity real-time facial reenactment at 20 FPS.
citing papers explorer
-
Chehre: An Emoji-Prompted Video Dataset for Perceptually Diverse Facial Expression Recognition
Chehre introduces a new emoji-prompted video dataset with multi-annotator labels to benchmark models on dominant and distributional facial expression recognition tasks.
-
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.
-
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.
-
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.
-
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.
-
Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization
Omni-Attribute is a new open-vocabulary image attribute encoder trained on semantically linked pairs with dual objectives to produce disentangled representations for personalization and compositional generation.
-
Unmasking Puppeteers: Leveraging Biometric Leakage to Expose Impersonation in AI-Based Videoconferencing
A pose-conditioned large-margin contrastive encoder isolates persistent biometric identity cues from transmitted latents in talking-head videoconferencing to flag impersonation attacks via cosine similarity without inspecting the output video.
-
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.
-
Durian: Dual Reference Image-Guided Portrait Animation with Attribute Transfer
Durian introduces a dual-reference diffusion model trained via self-reconstruction on video frames to enable cross-identity attribute transfer in portrait animations, supporting multi-attribute composition and interpolation.
-
Towards Flexible, Natural, Efficient Interaction for Conversational Talking Face Generation
InterTalk generates real-time multi-participant conversational talking-face videos by iteratively refining each person's lip, eye, and head motions from other participants' audio and motion feedback.
-
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.
-
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.
-
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.
-
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.
-
TOPOS: High-Fidelity and Efficient Industry-Grade 3D Head Generation
TOPOS creates high-fidelity 3D heads with fixed industry topology from single images via a specialized VAE with Perceiver Resampler and a rectified flow transformer.
-
The Alpha Blending Hypothesis: Compositing Shortcut in Deepfake Detection
Deepfake detectors act as alpha blending searchers; training solely on self-blended real images yields top cross-dataset generalization on 15 datasets without using synthetic deepfakes.
-
SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation
SocialDirector uses spatiotemporal actor masking and directional reweighting on cross-attention maps to reduce actor-action mismatches and improve target-directed interactions in generated multi-person videos.
-
MeshLAM: Feed-Forward One-Shot Animatable Textured Mesh Avatar Reconstruction
MeshLAM reconstructs high-fidelity animatable textured mesh head avatars from a single image via a feed-forward dual shape-texture architecture with iterative GRU decoding and reprojection-based guidance.
-
ARGen: Affect-Reinforced Generative Augmentation towards Vision-based Dynamic Emotion Perception
ARGen uses AU-guided prompts and a reinforcement-learned diffusion strategy to synthesize scarce-class facial expression videos that improve dynamic emotion recognition.
-
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.
-
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.
-
SteerFace: Debiasing Synthetic Face Generation via Adaptive Residue Perturbation
SteerFace perturbs identity embeddings toward random orthogonal directions on the hypersphere with an adaptive strategy to mitigate visual tendency in synthetic faces and improve downstream recognition performance.
-
EasyVFX: Frequency-Driven Decoupling for Resource-Efficient VFX Generation
EasyVFX decouples VFX generation via frequency-aware Mixture-of-Experts and test-time training to achieve realistic effects with limited resources.
-
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.
-
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.
-
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models
OpenWorldLib defines world models as perception-centered systems with interaction and long-term memory, and provides a modular inference codebase unifying interactive video, 3D, reasoning, and VLA tasks.
- Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling