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Models/InvPT

InvPT

Reported on 7 benchmarks across 6 tasks · 1 paper · 5 SOTA

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

Computer Vision6 results

Saliency DetectiononPASCAL Context
max_F1· 2022-03-15
84.81
SOTA
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding arXiv:2203.07997
Boundary DetectiononPASCAL Context
odsF· 2022-03-15
73
SOTA
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding arXiv:2203.07997
Boundary DetectiononNYU-Depth V2
odsF· 2022-03-15
78.1
SOTA
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding arXiv:2203.07997
Surface Normals EstimationonPASCAL Context
Mean Angle Error· 2022-03-15
14.15
SOTA
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding arXiv:2203.07997
Human ParsingonPASCAL Context
mIoU· 2022-03-15
67.61
SOTA
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding arXiv:2203.07997
Depth EstimationonNYU-Depth V2
RMSE· 2022-03-15
0.5183
best: 0.013 (Defocus/DepthNet (Normalized))
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding arXiv:2203.07997

Methodology1 result

3DonNYU-Depth V2
RMSE· 2022-03-15
0.5183
best: 0.013 (Defocus/DepthNet (Normalized))
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding arXiv:2203.07997