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DiverseAR: Boosting Diversity in Bitwise Autoregressive Image Generation
Ying Yang, Zhengyao Lv, Tianlin Pan +5
In this paper, we investigate the underexplored challenge of sample diversity in autoregressive (AR) generative models with bitwise visual tokenizers. We first analyze the factors…
Video-GPT via Next Clip Diffusion
Shaobin Zhuang, Zhipeng Huang, Ying Zhang +6
GPT has shown its remarkable success in natural language processing. However, the language sequence is not sufficient to describe spatial-temporal details in the visual world. Alte…
WeGen: A Unified Model for Interactive Multimodal Generation as We Chat
Zhipeng Huang, Shaobin Zhuang, Canmiao Fu +7
Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack th…
Get In Video: Add Anything You Want to the Video
Shaobin Zhuang, Zhipeng Huang, Binxin Yang +7
Video editing increasingly demands the ability to incorporate specific real-world instances into existing footage, yet current approaches fundamentally fail to capture the unique v…