Zhang, Yingya

Notice of Removal: VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

Luo, Z., Chen, D., Zhang, Y., Huang, Y., Wang, L., Shen, Y., Zhao, D., Zhou, J., & Tan, T. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

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ModelScope Text-to-Video Technical Report

Wang, J., Yuan, H., Chen, D., Zhang, Y., Wang, X., & Zhang, S. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 73

I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models

Zhang, S., Wang, J., Zhang, Y., Zhao, K., Yuan, H., Qin, Z., Wang, X., Zhao, D., & Zhou, J. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 22

DreamTalk: When Emotional Talking Head Generation Meets Diffusion Probabilistic Models

Ma, Y., Zhang, S., Wang, J., Wang, X., Zhang, Y., & Deng, Z. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 15

Wan: Open and Advanced Large-Scale Video Generative Models

Wan, T., Wang, A., Ai, B., Wen, B., Mao, C., Xie, C.-W., Chen, D., Yu, F., Zhao, H., Yang, J., et al. (2025) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 14