PAOLI: Pose-free Articulated Object Learning from Sparse-view Images

arXiv:2509.04276 · cs.CV · Submitted 2025-09-04 · Read on arXiv

cs.CV

Submitted: 2025-09-04

Updated: 2026-09-19

Terminology

• Gaussian Splatting — 15× in this paper · explained in 4 episodes
• 3D Gaussian Splatting — 10× in this paper · explained in 2 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Digital Twin — 5× in this paper · explained in 4 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Point Clouds — 4× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Chamfer Distance — 3× in this paper
• Consistency — 3× in this paper · explained in 3 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Alignment Problem — 2× in this paper · explained in 1 episode
• Angular Error — 2× in this paper · explained in 1 episode
• Gaussian Splatting (GS) — 2× in this paper · explained in 3 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• NeRF with Gaussian Splatting — 1× in this paper
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Peak Signal-to-Noise Ratio — 1× in this paper
• Point Cloud Data — 1× in this paper · explained in 2 episodes
• Segment Anything Model — 1× in this paper
• Segment Anything Model (SAM) — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• UFV-Splatter: Pose-Free Feed-Forward 3D Gaussian Splatting Adapted to Unfavorable Views
• Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model
• NAP: Neural 3D Articulation Prior
• No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images
• Weak antilocalization and localization in Eu$_2$Ir$_2$O$_7$ (111) thin films by reactive solid phase epitaxy
• SAM 2: Segment Anything in Images and Videos
• OPDMulti: Openable Part Detection for Multiple Objects
• NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

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