OVOW reconstructs instance-level, simulation-ready 4D mesh scenes from monocular video via a four-stage training-free pipeline and introduces a new benchmark for structured Video-to-4D evaluation.
In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
2 Pith papers cite this work. Polarity classification is still indexing.
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By injecting per-Gaussian motion variance and short-window temporal attention into the deformation network, MVFusion-GS improves dynamic-static decomposition and achieves top average metrics on Neu3D and NeRF On-the-go.
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One Video, One World: Turning Monocular Video into Physical 4D Scenes
OVOW reconstructs instance-level, simulation-ready 4D mesh scenes from monocular video via a four-stage training-free pipeline and introduces a new benchmark for structured Video-to-4D evaluation.
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MVFusion-GS: Motion-Variance Guided Temporal Attention for High-Quality Dynamic Gaussian Splatting
By injecting per-Gaussian motion variance and short-window temporal attention into the deformation network, MVFusion-GS improves dynamic-static decomposition and achieves top average metrics on Neu3D and NeRF On-the-go.