Revealing the Dark Secrets of Masked Image Modeling

Benchmark Model Rank Results
depth-estimation-on-nyu-depth-v2SwinV2-L 1K-MIM#3RMS: 0.287
depth-estimation-on-nyu-depth-v2SwinV2-B 1K-MIM#5RMS: 0.304
pose-estimation-on-crowdposeSwinV2-L 1K-MIM#4AP: 75.5
pose-estimation-on-crowdposeSwinV2-B 1K-MIM#5AP: 74.9
human-pose-keypoint-estimation-on-coco-test-devSwinV2-L 1K-MIM#15AP: 77.2
human-pose-keypoint-estimation-on-coco-test-devSwinV2-B 1K-MIM#20AP: 76.7
monocular-depth-estimation-on-kitti-eigen-splitSwinV2-L 1K-MIM#15absolute relative error: 0.050RMSE: 1.966Sq Rel: 0.139…
monocular-depth-estimation-on-kitti-eigen-splitSwinV2-B 1K-MIM#25absolute relative error: 0.052RMSE: 2.050Sq Rel: 0.148…
monocular-depth-estimation-on-nyu-depth-v2SwinV2-L 1K-MIM#27absolute relative error: 0.083RMSE: 0.287log 10: 0.035…
visual-object-tracking-on-lasotSwinV2-L 1K-MIM#31AUC: 70.7
visual-object-tracking-on-lasotSwinV2-B 1K-MIM#35AUC: 70
visual-object-tracking-on-got-10kSwinV2-L 1K-MIM#35Average Overlap: 72.9
visual-object-tracking-on-got-10kSwinV2-B 1K-MIM#39Average Overlap: 70.8