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RoboCloth dataset advances neural cloth material reconstruction

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced RoboCloth, a comprehensive dataset featuring 500 real cloth materials captured with robotic control over camera and lighting. This dataset enables neural reflectance reconstruction, allowing for the training of material priors. A two-stage pipeline demonstrates that a neural network trained on RoboCloth outperforms existing methods on both RoboCloth and the UBO2014 benchmark, showing strong generalization capabilities. AI

IMPACT This dataset could accelerate research in realistic material rendering for computer graphics and robotics.

RANK_REASON The cluster describes a new dataset and associated research paper for neural reflectance reconstruction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

RoboCloth dataset advances neural cloth material reconstruction

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The cluster describes a new dataset and associated research paper for neural reflectance reconstruction. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Zhen Li (Simon Fraser University), Haoran Qin (Westlake University), Francesco Di Sario (University of Torino,Simon Fraser University), Daniel Rebain (University of British Columbia,Wayve), Andrea Tagliasacchi (Simon Fraser University, Wayve,University o… ·

    RoboCloth: A Large-Scale Real Cloth Material Dataset for Neural Reflectance Reconstruction

    arXiv:2610.21090v1 Announce Type: new Abstract: We present RoboCloth, a dataset of 500 real cloth materials captured under flexible, calibrated camera and lighting configurations, where both are robotically controlled during acquisition. Each material is imaged in approximately 5…

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