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Models/ML-CrAIST-Li

ML-CrAIST-Li

Reported on 140 benchmarks across 4 tasks · 1 paper · 8 SOTA

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

Computer Vision70 results

Image Super-ResolutiononB100 - 2x upscaling
PSNR· 2024-08-19
32.36
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononB100 - 3x upscaling
PSNR· 2024-08-19
29.28
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononB100 - 2x upscaling
PSNR· 2024-08-19
32.36
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononB100 - 3x upscaling
PSNR· 2024-08-19
29.28
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-Resolutionon3x upscaling
#params (K)· 2024-08-19
749
best: 1268 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-Resolutionon3x upscaling
FLOPs(G)· 2024-08-19
49.6
best: 84.1 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet14 - 3x upscaling
PSNR· 2024-08-19
30.23
best: 31.55 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet14 - 3x upscaling
SSIM· 2024-08-19
0.8474
best: 0.8616 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-Resolutionon4x upscaling
#params (K)· 2024-08-19
758
best: 1280 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-Resolutionon4x upscaling
FLOPs(G)· 2024-08-19
25.5
best: 42.9 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet5 - 4x upscaling
PSNR· 2024-08-19
32.15
best: 33.38 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet5 - 4x upscaling
SSIM· 2024-08-19
0.8962
best: 0.9103 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet14 - 2x upscaling
PSNR· 2024-08-19
33.64
best: 35.36 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet14 - 2x upscaling
SSIM· 2024-08-19
0.9213
best: 0.9311 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet14 - 4x upscaling
PSNR· 2024-08-19
28.4
best: 29.54 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet14 - 4x upscaling
SSIM· 2024-08-19
0.7863
best: 0.894 (Edge-informed SR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet5 - 3x upscaling
PSNR· 2024-08-19
34.58
best: 35.35 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet5 - 3x upscaling
SSIM· 2024-08-19
0.9294
best: 0.938 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-Resolutionon2x upscaling
#params (K)· 2024-08-19
743
best: 1259 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-Resolutionon2x upscaling
FLOPs(G)· 2024-08-19
97.2
best: 165.7 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononB100 - 2x upscaling
SSIM· 2024-08-19
0.902
best: 0.9022 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononManga109 - 4x upscaling
PSNR· 2024-08-19
31.11
best: 33.19 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononManga109 - 4x upscaling
SSIM· 2024-08-19
0.9162
best: 0.9366 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononUrban100 - 2x upscaling
PSNR· 2024-08-19
32.93
best: 35.24 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononUrban100 - 2x upscaling
SSIM· 2024-08-19
0.9361
best: 0.9516 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononManga109 - 3x upscaling
PSNR· 2024-08-19
34.26
best: 36.12 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononManga109 - 3x upscaling
SSIM· 2024-08-19
0.9492
best: 0.9588 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononB100 - 4x upscaling
PSNR· 2024-08-19
27.73
best: 27.78 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet5 - 2x upscaling
PSNR· 2024-08-19
38.15
best: 39.14 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononSet5 - 2x upscaling
SSIM· 2024-08-19
0.9615
best: 0.9663 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononManga109 - 2x upscaling
PSNR· 2024-08-19
39.23
best: 41.22 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononManga109 - 2x upscaling
SSIM· 2024-08-19
0.9785
best: 0.9846 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononB100 - 3x upscaling
SSIM· 2024-08-19
0.8106
best: 0.8111 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2024-08-19
26.53
best: 28.72 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2024-08-19
0.8019
best: 0.9481 (SPSR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononUrban100 - 3x upscaling
PSNR· 2024-08-19
28.73
best: 31.07 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Image Super-ResolutiononUrban100 - 3x upscaling
SSIM· 2024-08-19
0.8651
best: 0.902 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-Resolutionon3x upscaling
#params (K)· 2024-08-19
749
best: 1268 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-Resolutionon3x upscaling
FLOPs(G)· 2024-08-19
49.6
best: 84.1 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet14 - 3x upscaling
PSNR· 2024-08-19
30.23
best: 31.55 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet14 - 3x upscaling
SSIM· 2024-08-19
0.8474
best: 0.8616 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-Resolutionon4x upscaling
#params (K)· 2024-08-19
758
best: 1280 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-Resolutionon4x upscaling
FLOPs(G)· 2024-08-19
25.5
best: 42.9 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet5 - 4x upscaling
PSNR· 2024-08-19
32.15
best: 33.38 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet5 - 4x upscaling
SSIM· 2024-08-19
0.8962
best: 0.9103 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet14 - 2x upscaling
PSNR· 2024-08-19
33.64
best: 35.36 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet14 - 2x upscaling
SSIM· 2024-08-19
0.9213
best: 0.9311 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet14 - 4x upscaling
PSNR· 2024-08-19
28.4
best: 29.54 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet14 - 4x upscaling
SSIM· 2024-08-19
0.7863
best: 0.894 (Edge-informed SR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet5 - 3x upscaling
PSNR· 2024-08-19
34.58
best: 35.35 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet5 - 3x upscaling
SSIM· 2024-08-19
0.9294
best: 0.938 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-Resolutionon2x upscaling
#params (K)· 2024-08-19
743
best: 1259 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-Resolutionon2x upscaling
FLOPs(G)· 2024-08-19
97.2
best: 165.7 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononB100 - 2x upscaling
SSIM· 2024-08-19
0.902
best: 0.9022 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononManga109 - 4x upscaling
PSNR· 2024-08-19
31.11
best: 33.19 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononManga109 - 4x upscaling
SSIM· 2024-08-19
0.9162
best: 0.9366 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononUrban100 - 2x upscaling
PSNR· 2024-08-19
32.93
best: 35.24 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononUrban100 - 2x upscaling
SSIM· 2024-08-19
0.9361
best: 0.9516 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononManga109 - 3x upscaling
PSNR· 2024-08-19
34.26
best: 36.12 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononManga109 - 3x upscaling
SSIM· 2024-08-19
0.9492
best: 0.9588 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononB100 - 4x upscaling
PSNR· 2024-08-19
27.73
best: 27.78 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet5 - 2x upscaling
PSNR· 2024-08-19
38.15
best: 39.14 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononSet5 - 2x upscaling
SSIM· 2024-08-19
0.9615
best: 0.9663 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononManga109 - 2x upscaling
PSNR· 2024-08-19
39.23
best: 41.22 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononManga109 - 2x upscaling
SSIM· 2024-08-19
0.9785
best: 0.9846 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononB100 - 3x upscaling
SSIM· 2024-08-19
0.8106
best: 0.8111 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2024-08-19
26.53
best: 28.72 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2024-08-19
0.8019
best: 0.9481 (SPSR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononUrban100 - 3x upscaling
PSNR· 2024-08-19
28.73
best: 31.07 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
3D Object Super-ResolutiononUrban100 - 3x upscaling
SSIM· 2024-08-19
0.8651
best: 0.902 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940

Graphs35 results

Super-ResolutiononB100 - 2x upscaling
PSNR· 2024-08-19
32.36
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononB100 - 3x upscaling
PSNR· 2024-08-19
29.28
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-Resolutionon3x upscaling
#params (K)· 2024-08-19
749
best: 1268 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-Resolutionon3x upscaling
FLOPs(G)· 2024-08-19
49.6
best: 84.1 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet14 - 3x upscaling
PSNR· 2024-08-19
30.23
best: 31.55 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet14 - 3x upscaling
SSIM· 2024-08-19
0.8474
best: 0.8616 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-Resolutionon4x upscaling
#params (K)· 2024-08-19
758
best: 1280 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-Resolutionon4x upscaling
FLOPs(G)· 2024-08-19
25.5
best: 42.9 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet5 - 4x upscaling
PSNR· 2024-08-19
32.15
best: 33.38 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet5 - 4x upscaling
SSIM· 2024-08-19
0.8962
best: 0.9103 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet14 - 2x upscaling
PSNR· 2024-08-19
33.64
best: 35.36 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet14 - 2x upscaling
SSIM· 2024-08-19
0.9213
best: 0.9311 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet14 - 4x upscaling
PSNR· 2024-08-19
28.4
best: 29.54 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet14 - 4x upscaling
SSIM· 2024-08-19
0.7863
best: 0.894 (Edge-informed SR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet5 - 3x upscaling
PSNR· 2024-08-19
34.58
best: 35.35 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet5 - 3x upscaling
SSIM· 2024-08-19
0.9294
best: 0.938 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-Resolutionon2x upscaling
#params (K)· 2024-08-19
743
best: 1259 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-Resolutionon2x upscaling
FLOPs(G)· 2024-08-19
97.2
best: 165.7 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononB100 - 2x upscaling
SSIM· 2024-08-19
0.902
best: 0.9022 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononManga109 - 4x upscaling
PSNR· 2024-08-19
31.11
best: 33.19 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononManga109 - 4x upscaling
SSIM· 2024-08-19
0.9162
best: 0.9366 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononUrban100 - 2x upscaling
PSNR· 2024-08-19
32.93
best: 35.24 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononUrban100 - 2x upscaling
SSIM· 2024-08-19
0.9361
best: 0.9516 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononManga109 - 3x upscaling
PSNR· 2024-08-19
34.26
best: 36.12 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononManga109 - 3x upscaling
SSIM· 2024-08-19
0.9492
best: 0.9588 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononB100 - 4x upscaling
PSNR· 2024-08-19
27.73
best: 27.78 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet5 - 2x upscaling
PSNR· 2024-08-19
38.15
best: 39.14 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononSet5 - 2x upscaling
SSIM· 2024-08-19
0.9615
best: 0.9663 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononManga109 - 2x upscaling
PSNR· 2024-08-19
39.23
best: 41.22 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononManga109 - 2x upscaling
SSIM· 2024-08-19
0.9785
best: 0.9846 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononB100 - 3x upscaling
SSIM· 2024-08-19
0.8106
best: 0.8111 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2024-08-19
26.53
best: 28.72 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2024-08-19
0.8019
best: 0.9481 (SPSR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononUrban100 - 3x upscaling
PSNR· 2024-08-19
28.73
best: 31.07 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
Super-ResolutiononUrban100 - 3x upscaling
SSIM· 2024-08-19
0.8651
best: 0.902 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940

Methodology35 results

16konB100 - 2x upscaling
PSNR· 2024-08-19
32.36
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konB100 - 3x upscaling
PSNR· 2024-08-19
29.28
SOTA
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16kon3x upscaling
#params (K)· 2024-08-19
749
best: 1268 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16kon3x upscaling
FLOPs(G)· 2024-08-19
49.6
best: 84.1 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet14 - 3x upscaling
PSNR· 2024-08-19
30.23
best: 31.55 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet14 - 3x upscaling
SSIM· 2024-08-19
0.8474
best: 0.8616 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16kon4x upscaling
#params (K)· 2024-08-19
758
best: 1280 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16kon4x upscaling
FLOPs(G)· 2024-08-19
25.5
best: 42.9 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet5 - 4x upscaling
PSNR· 2024-08-19
32.15
best: 33.38 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet5 - 4x upscaling
SSIM· 2024-08-19
0.8962
best: 0.9103 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet14 - 2x upscaling
PSNR· 2024-08-19
33.64
best: 35.36 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet14 - 2x upscaling
SSIM· 2024-08-19
0.9213
best: 0.9311 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet14 - 4x upscaling
PSNR· 2024-08-19
28.4
best: 29.54 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet14 - 4x upscaling
SSIM· 2024-08-19
0.7863
best: 0.894 (Edge-informed SR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet5 - 3x upscaling
PSNR· 2024-08-19
34.58
best: 35.35 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet5 - 3x upscaling
SSIM· 2024-08-19
0.9294
best: 0.938 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16kon2x upscaling
#params (K)· 2024-08-19
743
best: 1259 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16kon2x upscaling
FLOPs(G)· 2024-08-19
97.2
best: 165.7 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konB100 - 2x upscaling
SSIM· 2024-08-19
0.902
best: 0.9022 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konManga109 - 4x upscaling
PSNR· 2024-08-19
31.11
best: 33.19 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konManga109 - 4x upscaling
SSIM· 2024-08-19
0.9162
best: 0.9366 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konUrban100 - 2x upscaling
PSNR· 2024-08-19
32.93
best: 35.24 (HMA†)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konUrban100 - 2x upscaling
SSIM· 2024-08-19
0.9361
best: 0.9516 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konManga109 - 3x upscaling
PSNR· 2024-08-19
34.26
best: 36.12 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konManga109 - 3x upscaling
SSIM· 2024-08-19
0.9492
best: 0.9588 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konB100 - 4x upscaling
PSNR· 2024-08-19
27.73
best: 27.78 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet5 - 2x upscaling
PSNR· 2024-08-19
38.15
best: 39.14 (DRCT-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konSet5 - 2x upscaling
SSIM· 2024-08-19
0.9615
best: 0.9663 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konManga109 - 2x upscaling
PSNR· 2024-08-19
39.23
best: 41.22 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konManga109 - 2x upscaling
SSIM· 2024-08-19
0.9785
best: 0.9846 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konB100 - 3x upscaling
SSIM· 2024-08-19
0.8106
best: 0.8111 (ML-CrAIST)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konUrban100 - 4x upscaling
PSNR· 2024-08-19
26.53
best: 28.72 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konUrban100 - 4x upscaling
SSIM· 2024-08-19
0.8019
best: 0.9481 (SPSR)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konUrban100 - 3x upscaling
PSNR· 2024-08-19
28.73
best: 31.07 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940
16konUrban100 - 3x upscaling
SSIM· 2024-08-19
0.8651
best: 0.902 (Hi-IR-L)
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer arXiv:2408.09940