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Models/Unleashing Transformers (DINOv2)

Unleashing Transformers (DINOv2)

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

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

Medical6 results

  • Image GenerationonFFHQ 256 x 256
    Precision· 2021-11-24
    0.76
    best: 0.92 (LDM (DINOv2))
    SOTA
    Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesarXiv:2111.12701
  • Image GenerationonFFHQ 256 x 256
    FD· 2021-11-24
    393.45
    best: 592.26 (Projected-GAN (DINOv2))
    Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesarXiv:2111.12701
  • Image GenerationonFFHQ 256 x 256
    Recall· 2021-11-24
    0.24
    best: 0.76 (LDM (DINOv2))
    Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesarXiv:2111.12701
  • Image GenerationonLSUN Bedroom 256 x 256
    FD· 2021-11-24
    440.04
    best: 636.35 (Projected GAN (DINOv2))
    Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesarXiv:2111.12701
  • Image GenerationonLSUN Bedroom 256 x 256
    Precision· 2021-11-24
    0.78
    best: 0.85 (ADM (dropout, DINOv2))
    Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesarXiv:2111.12701
  • Image GenerationonLSUN Bedroom 256 x 256
    Recall· 2021-11-24
    0.41
    best: 0.75 (ADM (dropout, DINOv2))
    Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesarXiv:2111.12701