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Open Images

Benchmarks

Task NameDataset NameSOTA ResultTrend
Scene Graph GenerationOpen Images V6 (test)
wmAPrel56.38
74
Label PurityOpen Images
Label Purity79.6
30
Object DetectionOpen Images V7
Latency (us)95.1
30
Multi-label classificationOpen Images
mAP84.5
24
Multi-label ClassificationOpen Images (test)
mAP85
16
Feature Attribution EvaluationOpen Images 5000 random images (val)
AUC0.719
13
Object DetectionOpen Images unseen classes (non-overlapping)
AR@1000 (Overall)21
11
Multi-label classificationOpen Images v4 (test)
Precision (K=10)35.3
10
Attribution Quality EvaluationOpen Images (val)
SIC AUC0.866
10
Feature ReconstructionOpen Images clip_txt Original Target (test)
R^2 (variance-weighted)0.874
9
Multi-label classificationOpen Images (val)
mAP58.11
9
Instance SegmentationOpen Images (test)
mAP50 (Constrained Novel)35.9
8
Lossless Image CompressionOpen Images (val)
BPSP2.867
7
Concept AlignmentOpen Images hierarchy depth 5
Mean Jaccard Similarity0.8018
5
Concept recovery probing (1D logistic probe)Open Images 432 binary tasks (test)
CLIP Image Score0.6372
5
Visual Question AnsweringOpen Images cross-task (test)
Accuracy44.7
5
Visual ReasoningOpen Images (test)
Accuracy85.1
5
Scene Graph DetectionOpen Images V6
mR5040.7
5
Text-Label ClassificationOpen Images 3756 text labels
mAP82.52
4
Multi-label classificationOpen Images v6 (test)
mAP86.8
4
Multi-label classificationOpen Images v6
mAP (C)87.34
4
Object DetectionOpen Images 2.4K fashion photos V4 (test)
mAP72.7
4
Multi-label Generalized Zero-Shot ClassificationOpen Images proposed
P@1033.6
3
Multi-label Zero-Shot ClassificationOpen Images proposed (7186/367)
Precision @ K=33.5
3
Controlled Trace GenerationOpen Images Localized Narratives
LBM (k=0)0.212
3
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