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Step-Video-TI2V Technical Report: A State-of-the-Art Text-Driven Image-to-Video Generation Model

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arxiv 2503.11251 v1 pith:NQBMULFS submitted 2025-03-14 cs.CV cs.CL

classification cs.CVcs.CL
keywords step-video-ti2vimage-to-videogenerationstate-of-the-arttext-drivenmodelstep-video-ti2v-evaltask
verification ladder T0 review T1 audit T2 compute T3 formal

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We present Step-Video-TI2V, a state-of-the-art text-driven image-to-video generation model with 30B parameters, capable of generating videos up to 102 frames based on both text and image inputs. We build Step-Video-TI2V-Eval as a new benchmark for the text-driven image-to-video task and compare Step-Video-TI2V with open-source and commercial TI2V engines using this dataset. Experimental results demonstrate the state-of-the-art performance of Step-Video-TI2V in the image-to-video generation task. Both Step-Video-TI2V and Step-Video-TI2V-Eval are available at https://github.com/stepfun-ai/Step-Video-TI2V.

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Forward citations

Cited by 10 Pith papers

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