Every9D-21M supplies 21.8M real-world 9D pose annotations for 700 everyday categories by propagating manual canonical poses through cross-instance alignment in object-centric videos and verifying them multiview.
Orientation matters: Making 3d generative models orientation-aligned.arXiv preprint arXiv:2506.08640, 2025
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A coarse canonical mesh bottleneck plus multi-view consistency lets a shared object frame emerge from self-supervised training on in-the-wild videos without canonical labels or category conditioning.
FlowObject reformulates sparse-view 3D reconstruction as a training-free guided inverse problem in flow-matching models, augmented by 3DGS refinement to improve geometric completeness and fidelity.
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Every9D-21M: Large-Scale Real-World 9D Canonicalization of Everyday Objects
Every9D-21M supplies 21.8M real-world 9D pose annotations for 700 everyday categories by propagating manual canonical poses through cross-instance alignment in object-centric videos and verifying them multiview.