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.
Communications of the ACM65(1), 99–106 (2021)
4 Pith papers cite this work. Polarity classification is still indexing.
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TreeGaussian introduces a tree-guided cascaded contrastive framework that models hierarchical semantic relationships in 3D Gaussian scenes to improve consistent segmentation and understanding.
HSDF-Lane uses a height-aligned signed distance field with differentiable rendering and lane-aware semantic positional encoding to achieve SOTA 3D lane detection and height estimation on OpenLane.
SEGS constructs structural energy in the PCA subspace of U-Net features and injects its gradient into the denoising process to improve multi-view consistency in text-to-3D generation.
citing papers explorer
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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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TreeGaussian: Tree-Guided Cascaded Contrastive Learning for Hierarchical Consistent 3D Gaussian Scene Segmentation and Understanding
TreeGaussian introduces a tree-guided cascaded contrastive framework that models hierarchical semantic relationships in 3D Gaussian scenes to improve consistent segmentation and understanding.
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HSDF-Lane: Height-Aligned Signed Distance Field with Semantic Lane Prior for 3D Lane Detection
HSDF-Lane uses a height-aligned signed distance field with differentiable rendering and lane-aware semantic positional encoding to achieve SOTA 3D lane detection and height estimation on OpenLane.
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Structural Energy Guidance for View-Consistent Text-to-3D Generation
SEGS constructs structural energy in the PCA subspace of U-Net features and injects its gradient into the denoising process to improve multi-view consistency in text-to-3D generation.