Chehre introduces a new emoji-prompted video dataset with multi-annotator labels to benchmark models on dominant and distributional facial expression recognition tasks.
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Liveportrait: Efficient portrait animation with stitching and retargeting control
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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.