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20242026
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cs.CV2026

HunyuanImage 3.0 Technical Report

Tencent Hunyuan Foundation Model Team

We present HunyuanImage 3.0, a native multimodal model that unifies multimodal understanding and generation within an autoregressive framework, with its image generation module pub…

cs.CV2026

HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers

Guozhen Zhang, Xuerui Qiu, Yutao Cui +11

Holistic visual tokenizers are fundamental to unified multimodal models (UMMs) as they map diverse visual inputs into a unified representation space. In this paper, we present HYDR…

cs.CV2026

DisCa: Accelerating Video Diffusion Transformers with Distillation-Compatible Learnable Feature Caching

Chang Zou, Changlin Li, Yang Li +7

While diffusion models have achieved great success in the field of video generation, this progress is accompanied by a rapidly escalating computational burden. Among the existing a…

cs.CV2025

HunyuanVideo: A Systematic Framework For Large Video Generative Models

Weijie Kong, Qi Tian, Zijian Zhang +49

Recent advancements in video generation have significantly impacted daily life for both individuals and industries. However, the leading video generation models remain closed-sourc…

cs.CV2024

Ada-adapter:Fast Few-shot Style Personlization of Diffusion Model with Pre-trained Image Encoder

Jia Liu, Changlin Li, Qirui Sun +5

Fine-tuning advanced diffusion models for high-quality image stylization usually requires large training datasets and substantial computational resources, hindering their practical…

cs.CV2024

Perception-Oriented Video Frame Interpolation via Asymmetric Blending

Guangyang Wu, Xin Tao, Changlin Li +3

Previous methods for Video Frame Interpolation (VFI) have encountered challenges, notably the manifestation of blur and ghosting effects. These issues can be traced back to two piv…