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Models/CEVR

CEVR

Reported on 6 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Computer Vision6 results

  • inverse tone mappingonVDS dataset: Multi exposure stack-based inverse tone mapping
    HDR-VDP-2· 2023-09-07
    59
    SOTA
    Learning Continuous Exposure Value Representations for Single-Image HDR ReconstructionarXiv:2309.03900
  • inverse tone mappingonVDS dataset: Multi exposure stack-based inverse tone mapping
    Kim and Kautz TMO-PSNR· 2023-09-07
    30.04
    SOTA
    Learning Continuous Exposure Value Representations for Single-Image HDR ReconstructionarXiv:2309.03900
  • inverse tone mappingonVDS dataset: Multi exposure stack-based inverse tone mapping
    Reinhard'TMO-PSNR· 2023-09-07
    34.67
    best: 35.75 (Deep Conditional HDRI)
    SOTA
    Learning Continuous Exposure Value Representations for Single-Image HDR ReconstructionarXiv:2309.03900
  • Inverse-Tone-MappingonVDS dataset: Multi exposure stack-based inverse tone mapping
    HDR-VDP-2· 2023-09-07
    59
    SOTA
    Learning Continuous Exposure Value Representations for Single-Image HDR ReconstructionarXiv:2309.03900
  • Inverse-Tone-MappingonVDS dataset: Multi exposure stack-based inverse tone mapping
    Kim and Kautz TMO-PSNR· 2023-09-07
    30.04
    SOTA
    Learning Continuous Exposure Value Representations for Single-Image HDR ReconstructionarXiv:2309.03900
  • Inverse-Tone-MappingonVDS dataset: Multi exposure stack-based inverse tone mapping
    Reinhard'TMO-PSNR· 2023-09-07
    34.67
    best: 35.75 (Deep Conditional HDRI)
    SOTA
    Learning Continuous Exposure Value Representations for Single-Image HDR ReconstructionarXiv:2309.03900