Learning Discriminative Model Prediction for Tracking

Benchmark Model Rank Results
object-tracking-on-fe108DiMP#5Success Rate: 57.1Averaged Precision: 85.1
video-object-tracking-on-nv-vot211DiMP-50#18AUC: 35.89Precision: 48.68
visual-object-tracking-on-got-10kDiMP#39Average Overlap: 61.1Success Rate 0.5: 71.7
visual-object-tracking-on-lasotDiMP#42AUC: 56.8Normalized Precision: 65.0Precision: 56.7
visual-object-tracking-on-lasotDiMP-50#44Precision: 68.7
visual-object-tracking-on-trackingnetDiMP-50#31Accuracy: 74.0Normalized Precision: 80.1