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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
Unbiased Scene Graph Generation using Predicate Similarities—0
ALF: Adaptive Label Finetuning for Scene Graph Generation—0
FloCoDe: Unbiased Dynamic Scene Graph Generation with Temporal Consistency and Correlation Debiasing—0
Ensemble Predicate Decoding for Unbiased Scene Graph Generation—0
Unbiased Scene Graph Generation via Rich and Fair Semantic Extraction—0
Generalized Unbiased Scene Graph Generation—0
Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation—0
Learning Structured Representations of Visual Scenes—0
Unbiased Scene Graph Generation by Type-Aware Message Passing on Heterogeneous and Dual Graphs—0
Peer Learning for Unbiased Scene Graph Generation—0
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