March 11, 2024, 4:45 a.m. | Joseph Cho, Fachrina Dewi Puspitasari, Sheng Zheng, Jingyao Zheng, Lik-Hang Lee, Tae-Ho Kim, Choong Seon Hong, Chaoning Zhang

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.05131v1 Announce Type: cross
Abstract: Text-to-video generation marks a significant frontier in the rapidly evolving domain of generative AI, integrating advancements in text-to-image synthesis, video captioning, and text-guided editing. This survey critically examines the progression of text-to-video technologies, focusing on the shift from traditional generative models to the cutting-edge Sora model, highlighting developments in scalability and generalizability. Distinguishing our analysis from prior works, we offer an in-depth exploration of the technological frameworks and evolutionary pathways of these models. Additionally, we …

abstract agi arxiv captioning cs.ai cs.cv domain editing generative generative models image marks shift sora survey synthesis technologies text text-to-image text-to-video type video video generation world world model

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