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.
Orient anything: Learn- ing robust object orientation estimation from rendering 3d models
6 Pith papers cite this work. Polarity classification is still indexing.
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SATURN reconstructs approximate 3D scenes, derives soft perspective-aware predicates, and executes them symbolically to achieve stable performance on complex multi-perspective spatial grounding tasks where VLMs degrade.
ChopGrad truncates backpropagation to local frame windows in video diffusion models, reducing memory from linear in frame count to constant while enabling pixel-wise loss fine-tuning.
GenHSI is a training-free three-stage pipeline that turns a scene image, character image, and complex HSI prompt into long videos with plausible chained interactions by generating atomic actions, 3D keyframes via 2D inpainting plus optimization, and then feeding them to pre-trained video diffusion.
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.
Unposed-to-3D learns simulation-ready 3D vehicle models from unposed real images by predicting camera parameters for photometric self-supervision, then adding scale prediction and harmonization.
citing papers explorer
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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.
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SATURN: Symbolic Spatial Reasoning for Multi-Perspective Grounding
SATURN reconstructs approximate 3D scenes, derives soft perspective-aware predicates, and executes them symbolically to achieve stable performance on complex multi-perspective spatial grounding tasks where VLMs degrade.
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ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation
ChopGrad truncates backpropagation to local frame windows in video diffusion models, reducing memory from linear in frame count to constant while enabling pixel-wise loss fine-tuning.
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GenHSI: Controllable Generation of Human-Scene Interaction Videos
GenHSI is a training-free three-stage pipeline that turns a scene image, character image, and complex HSI prompt into long videos with plausible chained interactions by generating atomic actions, 3D keyframes via 2D inpainting plus optimization, and then feeding them to pre-trained video diffusion.
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Emergence of a Shared Canonical Object Frame from In-the-Wild Videos
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.
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Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images
Unposed-to-3D learns simulation-ready 3D vehicle models from unposed real images by predicting camera parameters for photometric self-supervision, then adding scale prediction and harmonization.