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From the 1 of 7 linked papers with an AI index.

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7 papers

cs.CV2026

Video = World + Event Stream

Lianghua Huang, Zhi-Fan Wu, Yupeng Shi +24

The paper introduces Wan-Streamer v0.3, a model that treats video as a combination of a persistent world and a dynamic event stream, enabling real-time multimodal audio‑visual inte…

cs.CV2026

Wan-Streamer v0.2: Higher Resolution, Same Latency

Lianghua Huang, Zhi-Fan Wu, Yupeng Shi +23

We present Wan-Streamer v0.2, a latency-preserving upgrade of the native-streaming, end-to-end audio-visual interaction model. v0.2 keeps the v0.1 modeling formulation, but raises…

cs.CV2026

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

Lianghua Huang, Zhi-Fan Wu, Wei Wang +22

We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex audio-visual interaction. W…

cs.AI2026

From Talking to Singing: A New Challenge for Audio-Visual Deepfake Detection

Ke Liu, Jiwei Wei, Wenyu Zhang +5

With rapid advances in audio-visual generative models, reliable forgery detection becomes increasingly critical. Existing methods for audio-visual deepfake detection typically rely…

cs.CV2026

AvatarForcing: One-Step Streaming Talking Avatars via Local-Future Sliding-Window Denoising

Liyuan Cui, Wentao Hu, Wenyuan Zhang +3

Real-time talking avatar generation requires low latency and minute-level temporal stability. Autoregressive (AR) forcing enables streaming inference but suffers from exposure bias…

cs.CV2025

Kling-Avatar: Grounding Multimodal Instructions for Cascaded Long-Duration Avatar Animation Synthesis

Yikang Ding, Jiwen Liu, Wenyuan Zhang +11

Recent advances in audio-driven avatar video generation have significantly enhanced audio-visual realism. However, existing methods treat instruction conditioning merely as low-lev…