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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 11–20 of 30 papers

TitleStatusHype
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 by Type-Aware Message Passing on Heterogeneous and Dual Graphs—0
Ensemble Predicate Decoding for Unbiased Scene Graph Generation—0
ALF: Adaptive Label Finetuning for Scene Graph Generation—0
FloCoDe: Unbiased Dynamic Scene Graph Generation with Temporal Consistency and Correlation Debiasing—0
Head-Tail Cooperative Learning Network for Unbiased Scene Graph GenerationCode0
Generalized Unbiased Scene Graph Generation—0
Unbiased Scene Graph Generation via Two-stage Causal Modeling—0
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