AI RESEARCH

OmniForcing: Unleashing Real-time Joint Audio-Visual Generation

arXiv CS.CV

ArXi:2603.11647v1 Announce Type: cross Recent joint audio-visual diffusion models achieve remarkable generation quality but suffer from high latency due to their bidirectional attention dependencies, hindering real-time applications. We propose OmniForcing, the first framework to distill an offline, dual-stream bidirectional diffusion model into a high-fidelity streaming autoregressive generator. However, naively applying causal distillation to such dual-stream architectures triggers severe