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cs.CV2026

Optimizing Few-Step Generation with Adaptive Matching Distillation

Lichen Bai, Zikai Zhou, Shitong Shao +5

Distribution Matching Distillation (DMD) is a powerful acceleration paradigm, yet its stability is often compromised in Forbidden Zone, regions where the real teacher provides unre…

cs.CV2026

NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation

Huichao Zhang, Liao Qu, Yiheng Liu +33

We present NextFlow, a unified decoder-only autoregressive transformer trained on 6 trillion interleaved text-image discrete tokens. By leveraging a unified vision representation w…

cs.CV2025

IMTalker: Efficient Audio-driven Talking Face Generation with Implicit Motion Transfer

Bo Chen, Tao Liu, Qi Chen +2

Talking face generation aims to synthesize realistic speaking portraits from a single image, yet existing methods often rely on explicit optical flow and local warping, which fail…

cs.CV2025

XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation

Bowen Chen, Mengyi Zhao, Haomiao Sun +4

Achieving fine-grained control over subject identity and semantic attributes (pose, style, lighting) in text-to-image generation, particularly for multiple subjects, often undermin…

cs.CV2024

GSTalker: Real-time Audio-Driven Talking Face Generation via Deformable Gaussian Splatting

Bo Chen, Shoukang Hu, Qi Chen +4

We present GStalker, a 3D audio-driven talking face generation model with Gaussian Splatting for both fast training (40 minutes) and real-time rendering (125 FPS) with a 35 m…