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Models/ViCE

ViCE

Reported on 12 benchmarks across 3 tasks · 1 paper · 10 SOTA

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

Medical4 results

Semantic SegmentationonCityscapes test
Accuracy· 2021-11-24
84.3
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
Semantic SegmentationonCOCO-Stuff-27
Clustering [Accuracy]· 2021-11-24
64.8
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
Semantic SegmentationonCOCO-Stuff-27
Clustering [mIoU]· 2021-11-24
21.77
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
Semantic SegmentationonCityscapes test
mIoU· 2021-11-24
25.2
best: 67.3 (EDANet)
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460

Computer Vision4 results

Unsupervised Semantic SegmentationonCityscapes test
Accuracy· 2021-11-24
84.3
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
Unsupervised Semantic SegmentationonCityscapes test
mIoU· 2021-11-24
25.2
best: 26.8 (CUPS)
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
Unsupervised Semantic SegmentationonCOCO-Stuff-27
Clustering [Accuracy]· 2021-11-24
64.8
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
Unsupervised Semantic SegmentationonCOCO-Stuff-27
Clustering [mIoU]· 2021-11-24
21.77
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460

Audio4 results

10-shot image generationonCityscapes test
Accuracy· 2021-11-24
84.3
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
10-shot image generationonCOCO-Stuff-27
Clustering [Accuracy]· 2021-11-24
64.8
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
10-shot image generationonCOCO-Stuff-27
Clustering [mIoU]· 2021-11-24
21.77
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
SOTA
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460
10-shot image generationonCityscapes test
mIoU· 2021-11-24
25.2
best: 67.3 (EDANet)
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment arXiv:2111.12460