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Unbiased Scene Graph Generation

Unbiased Scene Graph Generation (Unbiased SGG) aims to predict more informative scene graphs composed of more "tail predicates" *(in contrast to "head predicates" in terms of class frequencies) by dealing with the skewed, long-tailed predicate class distribution. (Definition from Chiou et al. "Recovering the Unbiased Scene Graphs from the Biased Ones")

Papers

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Showing 21–30 of 30 papers

TitleStatusHype
Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph GenerationCode0
Skew Class-balanced Re-weighting for Unbiased Scene Graph GenerationCode0
Peer Learning for Unbiased Scene Graph Generation—0
Unbiased Scene Graph Generation using Predicate Similarities—0
Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation—0
Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation—0
Rethinking the Evaluation of Unbiased Scene Graph Generation—0
Learning Structured Representations of Visual Scenes—0
PPDL: Predicate Probability Distribution Based Loss for Unbiased Scene Graph Generation—0
Unbiased Scene Graph Generation via Rich and Fair Semantic Extraction—0
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