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Models/GENESIS

GENESIS

Reported on 10 benchmarks across 3 tasks · 2 papers · 4 SOTA

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

Computer Vision6 results

Instance SegmentationonShelf&Tote Training Dataset
ARI· 2021-04-20
0.04
best: 0.55 (GENESIS-V2)
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958
Instance SegmentationonShapeStacks
ARI-FG· 2021-04-20
0.7
best: 0.82 (AST)
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958
Instance SegmentationonObjectsRoom
ARI-FG· 2021-04-20
0.63
best: 0.87 (AST)
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958
Unsupervised Object SegmentationonShelf&Tote Training Dataset
ARI· 2021-04-20
0.04
best: 0.55 (GENESIS-V2)
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958
Unsupervised Object SegmentationonShapeStacks
ARI-FG· 2021-04-20
0.7
best: 0.82 (AST)
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958
Unsupervised Object SegmentationonObjectsRoom
ARI-FG· 2021-04-20
0.63
best: 0.87 (AST)
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958

Medical4 results

Image GenerationonShapeStacks
FID· 2021-04-20
186.8
best: 112.7 (GENESIS-V2)
SOTA
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958
Image GenerationonObjectsRoom
FID· 2021-04-20
62.8
best: 52.6 (GENESIS-V2)
SOTA
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement arXiv:2104.09958
Image GenerationonGQN
FID· 2019-07-30
80.5
SOTA
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations arXiv:1907.13052
Image GenerationonMulti-dSprites
FID· 2019-07-30
24.9
SOTA
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations arXiv:1907.13052