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Models/CPAT

CPAT

Reported on 112 benchmarks across 4 tasks · 1 paper

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

Computer Vision56 results

Image Super-ResolutiononBSD100 - 2x upscaling
PSNR· 2024-07-23
32.64
best: 33.12 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononBSD100 - 2x upscaling
SSIM· 2024-07-23
0.9056
best: 0.9326 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet14 - 3x upscaling
PSNR· 2024-07-23
31.15
best: 31.55 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet14 - 3x upscaling
SSIM· 2024-07-23
0.8557
best: 0.8616 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet5 - 4x upscaling
PSNR· 2024-07-23
33.19
best: 33.38 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet5 - 4x upscaling
SSIM· 2024-07-23
0.9069
best: 0.9103 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet14 - 2x upscaling
PSNR· 2024-07-23
34.91
best: 35.36 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet14 - 2x upscaling
SSIM· 2024-07-23
0.9277
best: 0.9311 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet14 - 4x upscaling
PSNR· 2024-07-23
29.34
best: 29.54 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet14 - 4x upscaling
SSIM· 2024-07-23
0.7991
best: 0.894 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet5 - 3x upscaling
PSNR· 2024-07-23
35.16
best: 35.35 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet5 - 3x upscaling
SSIM· 2024-07-23
0.9334
best: 0.938 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononUrban100 - 2x upscaling
PSNR· 2024-07-23
34.76
best: 35.24 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononUrban100 - 2x upscaling
SSIM· 2024-07-23
0.9481
best: 0.9516 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononManga109 - 3x upscaling
PSNR· 2024-07-23
35.66
best: 36.12 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononManga109 - 3x upscaling
SSIM· 2024-07-23
0.9559
best: 0.9588 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet5 - 2x upscaling
PSNR· 2024-07-23
38.68
best: 39.14 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononSet5 - 2x upscaling
SSIM· 2024-07-23
0.9633
best: 0.9663 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononManga109 - 2x upscaling
PSNR· 2024-07-23
40.48
best: 41.22 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononManga109 - 2x upscaling
SSIM· 2024-07-23
0.9814
best: 0.9846 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2024-07-23
28.22
best: 28.72 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2024-07-23
0.8408
best: 0.9481 (SPSR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononUrban100 - 3x upscaling
PSNR· 2024-07-23
30.52
best: 31.07 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononUrban100 - 3x upscaling
SSIM· 2024-07-23
0.8923
best: 0.902 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2024-07-23
28.04
best: 28.16 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2024-07-23
0.7527
best: 0.851 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononBSD100 - 3x upscaling
PSNR· 2024-07-23
29.56
best: 29.67 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Image Super-ResolutiononBSD100 - 3x upscaling
SSIM· 2024-07-23
0.8174
best: 0.8256 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononBSD100 - 2x upscaling
PSNR· 2024-07-23
32.64
best: 33.12 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononBSD100 - 2x upscaling
SSIM· 2024-07-23
0.9056
best: 0.9326 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet14 - 3x upscaling
PSNR· 2024-07-23
31.15
best: 31.55 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet14 - 3x upscaling
SSIM· 2024-07-23
0.8557
best: 0.8616 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet5 - 4x upscaling
PSNR· 2024-07-23
33.19
best: 33.38 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet5 - 4x upscaling
SSIM· 2024-07-23
0.9069
best: 0.9103 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet14 - 2x upscaling
PSNR· 2024-07-23
34.91
best: 35.36 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet14 - 2x upscaling
SSIM· 2024-07-23
0.9277
best: 0.9311 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet14 - 4x upscaling
PSNR· 2024-07-23
29.34
best: 29.54 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet14 - 4x upscaling
SSIM· 2024-07-23
0.7991
best: 0.894 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet5 - 3x upscaling
PSNR· 2024-07-23
35.16
best: 35.35 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet5 - 3x upscaling
SSIM· 2024-07-23
0.9334
best: 0.938 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononUrban100 - 2x upscaling
PSNR· 2024-07-23
34.76
best: 35.24 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononUrban100 - 2x upscaling
SSIM· 2024-07-23
0.9481
best: 0.9516 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononManga109 - 3x upscaling
PSNR· 2024-07-23
35.66
best: 36.12 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononManga109 - 3x upscaling
SSIM· 2024-07-23
0.9559
best: 0.9588 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet5 - 2x upscaling
PSNR· 2024-07-23
38.68
best: 39.14 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononSet5 - 2x upscaling
SSIM· 2024-07-23
0.9633
best: 0.9663 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononManga109 - 2x upscaling
PSNR· 2024-07-23
40.48
best: 41.22 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononManga109 - 2x upscaling
SSIM· 2024-07-23
0.9814
best: 0.9846 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2024-07-23
28.22
best: 28.72 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2024-07-23
0.8408
best: 0.9481 (SPSR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononUrban100 - 3x upscaling
PSNR· 2024-07-23
30.52
best: 31.07 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononUrban100 - 3x upscaling
SSIM· 2024-07-23
0.8923
best: 0.902 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2024-07-23
28.04
best: 28.16 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2024-07-23
0.7527
best: 0.851 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononBSD100 - 3x upscaling
PSNR· 2024-07-23
29.56
best: 29.67 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
3D Object Super-ResolutiononBSD100 - 3x upscaling
SSIM· 2024-07-23
0.8174
best: 0.8256 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232

Graphs28 results

Super-ResolutiononBSD100 - 2x upscaling
PSNR· 2024-07-23
32.64
best: 33.12 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononBSD100 - 2x upscaling
SSIM· 2024-07-23
0.9056
best: 0.9326 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet14 - 3x upscaling
PSNR· 2024-07-23
31.15
best: 31.55 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet14 - 3x upscaling
SSIM· 2024-07-23
0.8557
best: 0.8616 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet5 - 4x upscaling
PSNR· 2024-07-23
33.19
best: 33.38 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet5 - 4x upscaling
SSIM· 2024-07-23
0.9069
best: 0.9103 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet14 - 2x upscaling
PSNR· 2024-07-23
34.91
best: 35.36 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet14 - 2x upscaling
SSIM· 2024-07-23
0.9277
best: 0.9311 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet14 - 4x upscaling
PSNR· 2024-07-23
29.34
best: 29.54 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet14 - 4x upscaling
SSIM· 2024-07-23
0.7991
best: 0.894 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet5 - 3x upscaling
PSNR· 2024-07-23
35.16
best: 35.35 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet5 - 3x upscaling
SSIM· 2024-07-23
0.9334
best: 0.938 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononUrban100 - 2x upscaling
PSNR· 2024-07-23
34.76
best: 35.24 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononUrban100 - 2x upscaling
SSIM· 2024-07-23
0.9481
best: 0.9516 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononManga109 - 3x upscaling
PSNR· 2024-07-23
35.66
best: 36.12 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononManga109 - 3x upscaling
SSIM· 2024-07-23
0.9559
best: 0.9588 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet5 - 2x upscaling
PSNR· 2024-07-23
38.68
best: 39.14 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononSet5 - 2x upscaling
SSIM· 2024-07-23
0.9633
best: 0.9663 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononManga109 - 2x upscaling
PSNR· 2024-07-23
40.48
best: 41.22 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononManga109 - 2x upscaling
SSIM· 2024-07-23
0.9814
best: 0.9846 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2024-07-23
28.22
best: 28.72 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2024-07-23
0.8408
best: 0.9481 (SPSR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononUrban100 - 3x upscaling
PSNR· 2024-07-23
30.52
best: 31.07 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononUrban100 - 3x upscaling
SSIM· 2024-07-23
0.8923
best: 0.902 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2024-07-23
28.04
best: 28.16 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2024-07-23
0.7527
best: 0.851 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononBSD100 - 3x upscaling
PSNR· 2024-07-23
29.56
best: 29.67 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
Super-ResolutiononBSD100 - 3x upscaling
SSIM· 2024-07-23
0.8174
best: 0.8256 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232

Methodology28 results

16konBSD100 - 2x upscaling
PSNR· 2024-07-23
32.64
best: 33.12 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konBSD100 - 2x upscaling
SSIM· 2024-07-23
0.9056
best: 0.9326 (WaveMixSR-V2)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet14 - 3x upscaling
PSNR· 2024-07-23
31.15
best: 31.55 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet14 - 3x upscaling
SSIM· 2024-07-23
0.8557
best: 0.8616 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet5 - 4x upscaling
PSNR· 2024-07-23
33.19
best: 33.38 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet5 - 4x upscaling
SSIM· 2024-07-23
0.9069
best: 0.9103 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet14 - 2x upscaling
PSNR· 2024-07-23
34.91
best: 35.36 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet14 - 2x upscaling
SSIM· 2024-07-23
0.9277
best: 0.9311 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet14 - 4x upscaling
PSNR· 2024-07-23
29.34
best: 29.54 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet14 - 4x upscaling
SSIM· 2024-07-23
0.7991
best: 0.894 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet5 - 3x upscaling
PSNR· 2024-07-23
35.16
best: 35.35 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet5 - 3x upscaling
SSIM· 2024-07-23
0.9334
best: 0.938 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konUrban100 - 2x upscaling
PSNR· 2024-07-23
34.76
best: 35.24 (HMA†)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konUrban100 - 2x upscaling
SSIM· 2024-07-23
0.9481
best: 0.9516 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konManga109 - 3x upscaling
PSNR· 2024-07-23
35.66
best: 36.12 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konManga109 - 3x upscaling
SSIM· 2024-07-23
0.9559
best: 0.9588 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet5 - 2x upscaling
PSNR· 2024-07-23
38.68
best: 39.14 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konSet5 - 2x upscaling
SSIM· 2024-07-23
0.9633
best: 0.9663 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konManga109 - 2x upscaling
PSNR· 2024-07-23
40.48
best: 41.22 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konManga109 - 2x upscaling
SSIM· 2024-07-23
0.9814
best: 0.9846 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konUrban100 - 4x upscaling
PSNR· 2024-07-23
28.22
best: 28.72 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konUrban100 - 4x upscaling
SSIM· 2024-07-23
0.8408
best: 0.9481 (SPSR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konUrban100 - 3x upscaling
PSNR· 2024-07-23
30.52
best: 31.07 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konUrban100 - 3x upscaling
SSIM· 2024-07-23
0.8923
best: 0.902 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konBSD100 - 4x upscaling
PSNR· 2024-07-23
28.04
best: 28.16 (DRCT-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konBSD100 - 4x upscaling
SSIM· 2024-07-23
0.7527
best: 0.851 (Edge-informed SR)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konBSD100 - 3x upscaling
PSNR· 2024-07-23
29.56
best: 29.67 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232
16konBSD100 - 3x upscaling
SSIM· 2024-07-23
0.8174
best: 0.8256 (Hi-IR-L)
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution arXiv:2407.16232