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20242026
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cs.CV2026

Vidu S1: A Real-Time Interactive Video Generation Model

Jintao Zhang, Kai Jiang, Jintao Chen +24

We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment throug…

cs.CV2026

minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models

Min Zhao, Hongzhou Zhu, Bokai Yan +9

Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time interactive video world models remains…

cs.CV2025

Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator

Kaiwen Zheng, Yongxin Chen, Huayu Chen +4

While likelihood-based generative models, particularly diffusion and autoregressive models, have achieved remarkable fidelity in visual generation, the maximum likelihood estimatio…

cs.CV2025

DiffGAP: A Lightweight Diffusion Module in Contrastive Space for Bridging Cross-Model Gap

Shentong Mo, Zehua Chen, Fan Bao +1

Recent works in cross-modal understanding and generation, notably through models like CLAP (Contrastive Language-Audio Pretraining) and CAVP (Contrastive Audio-Visual Pretraining),…

cs.CV2024

Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models

Fan Bao, Chendong Xiang, Gang Yue +7

We introduce Vidu, a high-performance text-to-video generator that is capable of producing 1080p videos up to 16 seconds in a single generation. Vidu is a diffusion model with U-Vi…