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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
Fine-Grained Scene Graph Generation with Data TransferCode1
Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph GenerationCode1
Resistance Training using Prior Bias: toward Unbiased Scene Graph GenerationCode1
PPDL: Predicate Probability Distribution Based Loss for Unbiased Scene Graph Generation—0
Recovering the Unbiased Scene Graphs from the Biased OnesCode1
Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph GenerationCode1
CogTree: Cognition Tree Loss for Unbiased Scene Graph GenerationCode1
PCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph GenerationCode1
Unbiased Scene Graph Generation from Biased TrainingCode2
Unbiased Scene Graph Generation via Rich and Fair Semantic Extraction—0
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