Illuminant Estimation on NUS-8 (test)
2.07Mean ErrorVLM-CC
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| VLM-CCTrain dataset=Gehler-Shi2026.05 | 2.07 | 1.72 | 1.76 | 0.62 | 4.11 | |
| CCMNetTrain dataset=Gehler-Shi2026.05 | 2.17 | 1.65 | 1.76 | 0.59 | 4.75 | |
| C4-SqueezeNet-FC4Train dataset=Gehler-Shi2026.05 | 2.28 | 1.9 | 1.97 | 0.67 | 4.6 | |
| GCCTrain dataset=Gehler-Shi2026.05 | 2.38 | 2.01 | 2.1 | 0.8 | 4.58 | |
| SqueezeNet-FC4Train dataset=Gehler-Shi2026.05 | 2.4 | 2.03 | 2.1 | 0.7 | 4.8 | |
| C5Train dataset=Gehler-Shi2026.05 | 2.65 | 1.98 | 2.14 | 0.66 | 5.72 | |
| GITrain dataset=Gehler-Shi2026.05 | 2.91 | 1.97 | 2.13 | 0.56 | 6.67 | |
| Cheng et al.Train dataset=Gehler-Shi2026.05 | 2.92 | 2.04 | 2.24 | 0.62 | 6.61 | |
| Gray Pixel (edge)Train dataset=Gehler-Shi2026.05 | 3.15 | 2.2 | — | — | — | |
| FFCCTrain dataset=Gehler-Shi2026.05 | 3.19 | 2.33 | 2.52 | 0.84 | 7.01 | |
| General Gray-WorldTrain dataset=Gehler-Shi2026.05 | 3.2 | 2.56 | 2.68 | 0.85 | 6.68 | |
| 1st-order Gray-EdgeTrain dataset=Gehler-Shi2026.05 | 3.35 | 2.58 | 2.76 | 0.79 | 7.18 | |
| 2nd-order Gray-EdgeTrain dataset=Gehler-Shi2026.05 | 3.36 | 2.7 | 2.8 | 0.89 | 7.14 | |
| CLCCTrain dataset=Gehler-Shi2026.05 | 3.42 | 2.95 | 3.06 | 0.94 | 6.7 | |
| LSRSTrain dataset=Gehler-Shi2026.05 | 3.45 | 2.51 | 2.7 | 0.98 | 7.32 | |
| BayesianTrain dataset=Gehler-Shi2026.05 | 3.65 | 3.08 | 3.16 | 1.03 | 7.33 | |
| Shades-of-GrayTrain dataset=Gehler-Shi2026.05 | 3.67 | 2.94 | 3.03 | 0.99 | 7.75 | |
| ChakrabartiTrain dataset=Gehler-Shi2026.05 | 3.89 | 3.1 | 3.26 | 1.17 | 7.95 | |
| SIIETrain dataset=Gehler-Shi2026.05 | 4.24 | 3.88 | 3.93 | 1.45 | 7.66 | |
| Gray-WorldTrain dataset=Gehler-Shi2026.05 | 4.59 | 3.46 | 3.81 | 1.16 | 9.85 | |
| White-PatchTrain dataset=Gehler-Shi2026.05 | 9.91 | 7.44 | 8.78 | 1.44 | 21.27 |