AI RESEARCH
Making Video Models Adhere to User Intent with Minor Adjustments
arXiv CS.CV
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ArXi:2603.19672v1 Announce Type: new With the recent drastic advancements in text-to-video diffusion models, controlling their generations has drawn interest. A popular way for control is through bounding boxes or layouts. However, enforcing adherence to these control inputs is still an open problem. In this work, we show that by slightly adjusting user-provided bounding boxes we can improve both the quality of generations and the adherence to the control inputs.