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20232026
most citedMoVA: Adapting Mixture of Vision Experts to Multimodal Context

6 citations · 9 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024★ 1 cited

VividFace: A Diffusion-Based Hybrid Framework for High-Fidelity Video Face Swapping

Hao Shao, Shulun Wang, Yang Zhou +7

Video face swapping is becoming increasingly popular across various applications, yet existing methods primarily focus on static images and struggle with video face swapping becaus…

cs.CV2024

EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM

Zhuofan Zong, Dongzhi Jiang, Bingqi Ma +5

Significant achievements in personalization of diffusion models have been witnessed. Conventional tuning-free methods mostly encode multiple reference images by averaging their ima…

cs.CV2024

Pretrained Reversible Generation as Unsupervised Visual Representation Learning

Rongkun Xue, Jinouwen Zhang, Yazhe Niu +4

Recent generative models based on score matching and flow matching have significantly advanced generation tasks, but their potential in discriminative tasks remains underexplored.…

cs.CV2024★ 2 cited

Exploring the Role of Large Language Models in Prompt Encoding for Diffusion Models

Bingqi Ma, Zhuofan Zong, Guanglu Song +2

Large language models (LLMs) based on decoder-only transformers have demonstrated superior text understanding capabilities compared to CLIP and T5-series models. However, the parad…

cs.CV2024★ 6 cited

MoVA: Adapting Mixture of Vision Experts to Multimodal Context

Zhuofan Zong, Bingqi Ma, Dazhong Shen +5

As the key component in multimodal large language models (MLLMs), the ability of the visual encoder greatly affects MLLM's understanding on diverse image content. Although some lar…