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Models/ATOM(Resnet18)+EnergyRegression

ATOM(Resnet18)+EnergyRegression

Reported on 8 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Computer Vision8 results

Object TrackingonUAV123
AUC· 2019-09-26
0.672
best: 0.739 (LoRAT-g-378)
SOTA
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297
Object TrackingonTrackingNet
Precision· 2019-09-26
69.7
best: 89.2 (MCITrack-L384)
SOTA
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297
Object TrackingonTrackingNet
Success Rate· 2019-09-26
74.5
SOTA
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297
Visual Object TrackingonUAV123
AUC· 2019-09-26
0.672
best: 0.739 (LoRAT-g-378)
SOTA
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297
Visual Object TrackingonTrackingNet
Precision· 2019-09-26
69.7
best: 89.2 (MCITrack-L384)
SOTA
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297
Visual Object TrackingonTrackingNet
Success Rate· 2019-09-26
74.5
SOTA
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297
Object TrackingonTrackingNet
Normalized Precision· 2019-09-26
80.1
best: 92.1 (MCITrack-L384)
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297
Visual Object TrackingonTrackingNet
Normalized Precision· 2019-09-26
80.1
best: 92.1 (MCITrack-L384)
Energy-Based Models for Deep Probabilistic Regression arXiv:1909.12297