TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/3D-VAE-GAN

3D-VAE-GAN

Reported on 6 benchmarks across 1 task · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology6 results

  • 3DonPix3D
    R@1· 2016-10-24
    0.02
    best: 0.53 (MarrNet extension (w/o Pose))
    SOTA
    Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingarXiv:1610.07584
  • 3DonPix3D
    R@16· 2016-10-24
    0.21
    best: 0.85 (MarrNet extension (w/o Pose))
    SOTA
    Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingarXiv:1610.07584
  • 3DonPix3D
    R@2· 2016-10-24
    0.03
    best: 0.62 (MarrNet extension (w/o Pose))
    SOTA
    Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingarXiv:1610.07584
  • 3DonPix3D
    R@32· 2016-10-24
    0.34
    best: 0.9 (MarrNet extension (w/o Pose))
    SOTA
    Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingarXiv:1610.07584
  • 3DonPix3D
    R@4· 2016-10-24
    0.07
    best: 0.71 (MarrNet extension (w/o Pose))
    SOTA
    Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingarXiv:1610.07584
  • 3DonPix3D
    R@8· 2016-10-24
    0.12
    best: 0.78 (MarrNet extension (w/o Pose))
    SOTA
    Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingarXiv:1610.07584