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cs.CV2026

TransText: Alpha-as-RGB Representation for Transparent Text Animation

Fei Zhang, Zijian Zhou, Bohao Tang +9

We introduce the first method, to the best of our knowledge, for adapting image-to-video models to layer-aware text (glyph) animation, a capability critical for practical dynamic v…

cs.CV2026

Mixture of States: Routing Token-Level Dynamics for Multimodal Generation

Haozhe Liu, Ding Liu, Mingchen Zhuge +16

We introduce MoS (Mixture of States), a novel fusion paradigm for multimodal diffusion models that merges modalities using flexible, state-based interactions. The core of MoS is a…

cs.CV2025

HiStream: Efficient High-Resolution Video Generation via Redundancy-Eliminated Streaming

Haonan Qiu, Shikun Liu, Zijian Zhou +10

High-resolution video generation, while crucial for digital media and film, is computationally bottlenecked by the quadratic complexity of diffusion models, making practical infere…

cs.CV2025

OneStory: Coherent Multi-Shot Video Generation with Adaptive Memory

Zhaochong An, Menglin Jia, Haonan Qiu +12

Storytelling in real-world videos often unfolds through multiple shots -- discontinuous yet semantically connected clips that together convey a coherent narrative. However, existin…

cs.CV2025

Scaling Zero-Shot Reference-to-Video Generation

Zijian Zhou, Shikun Liu, Haozhe Liu +14

Reference-to-video (R2V) generation aims to synthesize videos that align with a text prompt while preserving the subject identity from reference images. However, current R2V method…

cs.CV2025

TUNA: Taming Unified Visual Representations for Native Unified Multimodal Models

Zhiheng Liu, Weiming Ren, Haozhe Liu +22

Unified multimodal models (UMMs) aim to jointly perform multimodal understanding and generation within a single framework. We present TUNA, a native UMM that builds a unified conti…