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Models/U-TAE + PaPs

U-TAE + PaPs

Reported on 9 benchmarks across 3 tasks · 1 paper · 9 SOTA

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

Medical3 results

Semantic SegmentationonPASTIS
PQ· 2021-07-16
40.4
best: 52.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933
Semantic SegmentationonPASTIS
RQ· 2021-07-16
49.2
best: 61.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933
Semantic SegmentationonPASTIS
SQ· 2021-07-16
81.3
best: 84.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933

Audio3 results

10-shot image generationonPASTIS
PQ· 2021-07-16
40.4
best: 52.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933
10-shot image generationonPASTIS
RQ· 2021-07-16
49.2
best: 61.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933
10-shot image generationonPASTIS
SQ· 2021-07-16
81.3
best: 84.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933

Computer Vision3 results

Panoptic SegmentationonPASTIS
PQ· 2021-07-16
40.4
best: 52.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933
Panoptic SegmentationonPASTIS
RQ· 2021-07-16
49.2
best: 61.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933
Panoptic SegmentationonPASTIS
SQ· 2021-07-16
81.3
best: 84.6 (Exchanger+Mask2Former)
SOTA
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks arXiv:2107.07933