Generating videos of a specific subject from a few reference images remains challenging when the camera reveals surfaces that are not visible in the input. Early subject-to-video (S2V) methods conditi
OmniShowcase improves subject-to-video generation by using geometry-driven training data and surface-normal conditioning to maintain 3D consistency across novel viewpoints.
Generating videos of a specific subject from a few reference images remains challenging when the camera reveals surfaces that are not visible in the input. Early subject-to-video (S2V) methods condition on a single reference image and must therefore infer the subject's unseen appearance and geometry as the viewpoint changes. To address this limitation, recent methods extend S2V to multiple reference views, providing more information about the subject from different viewpoints. However, they do not explicitly specify the 3D structure that connects these observations. In addition, existing training data do not guarantee that viewpoint changes preserve the same underlying 3D subject. We…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
OmniShowcase: Omnidirectional Subject-Consistent Video Generation from Multi-View Images was first seen on Hugging Face · Daily papers on Oct 29, 2026. Since then it has appeared in 18 checks on 2 different days. Its best position was #4 of 30, reached on Oct 30, 05:28 UTC. It dropped off the list after Oct 30, 15:28 UTC.
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#4 on Hugging Face · Daily papers, on Oct 30, 05:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 29, 2026 and has been on the list on 2 days (18 checks) since.