Research map / 3D vision / Depth and stereo
Video Stitching from Multiple Moving Cameras
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Proposes MViS, a lightweight test-time optimization framework for geometric alignment of videos of the same scene captured by multiple freely moving cameras, with temporal consistency.
Problem
Geometric video alignment for the same scene captured by multiple freely moving cameras; existing image stitching or video stabilization methods are limited to two cameras or assume a fixed linear camera ordering.
Approach
A test-time optimization framework performing joint multi-view alignment across freely moving cameras without requiring a fixed linear ordering, while enforcing temporal consistency.
Experimental setup
Builds on: image stitching video stabilization
Closest papers by meaning
- Learning to Correct Geometry in Generated Videos (NeurIPS 2026 · similarity 0.88)
- Direct Photometric Alignment by Mesh Deformation (CVPR 2017 · similarity 0.87)
- SynCamMaster: Synchronizing Multi-Camera Video Generation from Diverse Viewpoints (ICLR 2025 · similarity 0.86)
- Visual Sync: Multi‑Camera Synchronization via Cross‑View Object Motion (NeurIPS 2025 · similarity 0.85)
- MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing (NeurIPS 2024 · similarity 0.85)
- MultiDiff: Consistent Novel View Synthesis from a Single Image (CVPR 2024 · similarity 0.85)
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