GeoNeXt repurposes pretrained video generative models for geometry-estimation tasks such as depth and surface-normal prediction by formulating geometry estimation as a next-frames prediction task. Leveraging the structured knowledge already present in video models allows more data-efficient learning, reaching performance comparable to discriminative methods trained on substantially larger datasets.
