LumiSculpt: A Consistency Lighting Control Network for Video Generation

• URL: http://arxiv.org/abs/2410.22979v1
• Date: Wed, 30 Oct 2024 12:44:08 GMT
• Title: LumiSculpt: A Consistency Lighting Control Network for Video Generation
• Authors: Yuxin Zhang, Dandan Zheng, Biao Gong, Jingdong Chen, Ming Yang, Weiming Dong, Changsheng Xu,
• Abstract summary: Lighting plays a pivotal role in ensuring the naturalness of video generation. It remains challenging to disentangle and model independent and coherent lighting attributes. LumiSculpt enables precise and consistent lighting control in T2V generation models.
• Score: 67.48791242688493
• License:
• Abstract: Lighting plays a pivotal role in ensuring the naturalness of video generation, significantly influencing the aesthetic quality of the generated content. However, due to the deep coupling between lighting and the temporal features of videos, it remains challenging to disentangle and model independent and coherent lighting attributes, limiting the ability to control lighting in video generation. In this paper, inspired by the established controllable T2I models, we propose LumiSculpt, which, for the first time, enables precise and consistent lighting control in T2V generation models.LumiSculpt equips the video generation with strong interactive capabilities, allowing the input of custom lighting reference image sequences. Furthermore, the core learnable plug-and-play module of LumiSculpt facilitates remarkable control over lighting intensity, position, and trajectory in latent video diffusion models based on the advanced DiT backbone.Additionally, to effectively train LumiSculpt and address the issue of insufficient lighting data, we construct LumiHuman, a new lightweight and flexible dataset for portrait lighting of images and videos. Experimental results demonstrate that LumiSculpt achieves precise and high-quality lighting control in video generation.

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