Papers Unbiased Scene Graph Generation
“Unbiased Scene Graph Generation” 태그가 달린 논문 32편 · 필터 해제
SGG-R$^{\rm 3}$: From Next-Token Prediction to End-to-End Unbiased Scene Graph Generation
Scene Graph Generation (SGG) structures visual scenes as graphs of objects and their relations. While Multimodal Large Language Models (MLLMs) have advanced end-to-end SGG, current methods are hindered by both a lack of …
Unbiased Scene Graph GenerationReinforcement LearningSalience-SGG: Enhancing Unbiased Scene Graph Generation with Iterative Salience Estimation
Scene Graph Generation (SGG) suffers from a long-tailed distribution, where a few predicate classes dominate while many others are underrepresented, leading to biased models that underperform on rare relations. Unbiased-…
Unbiased Scene Graph GenerationUnbiased Scene Graph Generation by Type-Aware Message Passing on Heterogeneous and Dual Graphs
Although great progress has been made in the research of unbiased scene graph generation, issues still hinder improving the predictive performance of both head and tail classes. An unbiased scene graph generation (TA-HDG…
graph constructionGraph GenerationScene Graph GenerationUnbiased Scene Graph GenerationEnsemble Predicate Decoding for Unbiased Scene Graph Generation
Scene Graph Generation (SGG) aims to generate a comprehensive graphical representation that accurately captures the semantic information of a given scenario. However, the SGG model's performance in predicting more fine-g…
Graph GenerationScene Graph GenerationUnbiased Scene Graph GenerationSemantic Diversity-aware Prototype-based Learning for Unbiased Scene Graph Generation
The scene graph generation (SGG) task involves detecting objects within an image and predicting predicates that represent the relationships between the objects. However, in SGG benchmark datasets, each subject-object pai…
DiversityGraph GenerationScene Graph GenerationUnbiased Scene Graph GenerationALF: Adaptive Label Finetuning for Scene Graph Generation
Scene Graph Generation (SGG) endeavors to predict the relationships between subjects and objects in a given image. Nevertheless, the long-tail distribution of relations often leads to biased prediction on coarse labels, …
Graph GenerationRelationScene Graph GenerationUnbiased Scene Graph GenerationFloCoDe: Unbiased Dynamic Scene Graph Generation with Temporal Consistency and Correlation Debiasing
Dynamic scene graph generation (SGG) from videos requires not only a comprehensive understanding of objects across scenes but also a method to capture the temporal motions and interactions with different objects. Moreove…
Graph GenerationScene Graph GenerationUnbiased Scene Graph GenerationHead-Tail Cooperative Learning Network for Unbiased Scene Graph Generation
Scene Graph Generation (SGG) as a critical task in image understanding, facing the challenge of head-biased prediction caused by the long-tail distribution of predicates. However, current unbiased SGG methods can easily …
Graph GenerationPredictionScene Graph GenerationSelf-Supervised Learning+1Vision Relation Transformer for Unbiased Scene Graph Generation
Recent years have seen a growing interest in Scene Graph Generation (SGG), a comprehensive visual scene understanding task that aims to predict entity relationships using a relation encoder-decoder pipeline stacked on to…
DecoderGraph GenerationRelationScene Graph Generation+2Compositional Feature Augmentation for Unbiased Scene Graph Generation
Scene Graph Generation (SGG) aims to detect all the visual relation triplets <sub, pred, obj> in a given image. With the emergence of various advanced techniques for better utilizing both the intrinsic and extrinsic info…
DiversityGraph GenerationRelationScene Graph Generation+2Generalized Unbiased Scene Graph Generation
Existing Unbiased Scene Graph Generation (USGG) methods only focus on addressing the predicate-level imbalance that high-frequency classes dominate predictions of rare ones, while overlooking the concept-level imbalance.…
Graph GenerationScene Graph GenerationUnbiased Scene Graph GenerationUnbiased Scene Graph Generation via Two-stage Causal Modeling
Despite the impressive performance of recent unbiased Scene Graph Generation (SGG) methods, the current debiasing literature mainly focuses on the long-tailed distribution problem, whereas it overlooks another source of …
Causal InferenceGraph GenerationRepresentation LearningScene Graph Generation+1Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph Generation
This paper investigates the problem of scene graph generation in videos with the aim of capturing semantic relations between subjects and objects in the form of $\langle$subject, predicate, object$\rangle$ triplets. Reco…
Graph GenerationMeta-LearningScene Graph GenerationUnbiased Scene Graph GenerationUnbiased Scene Graph Generation in Videos
The task of dynamic scene graph generation (SGG) from videos is complicated and challenging due to the inherent dynamics of a scene, temporal fluctuation of model predictions, and the long-tailed distribution of the visu…
Graph GenerationScene Graph GenerationUnbiased Scene Graph GenerationSkew Class-balanced Re-weighting for Unbiased Scene Graph Generation
An unbiased scene graph generation (SGG) algorithm referred to as Skew Class-balanced Re-weighting (SCR) is proposed for considering the unbiased predicate prediction caused by the long-tailed distribution. The prior wor…
Graph GenerationScene Graph GenerationUnbiased Scene Graph GenerationPeer Learning for Unbiased Scene Graph Generation
Unbiased scene graph generation (USGG) is a challenging task that requires predicting diverse and heavily imbalanced predicates between objects in an image. To address this, we propose a novel framework peer learning tha…
Graph GenerationScene Graph GenerationUnbiased Scene Graph GenerationUnbiased Scene Graph Generation using Predicate Similarities
Scene Graphs are widely applied in computer vision as a graphical representation of relationships between objects shown in images. However, these applications have not yet reached a practical stage of development owing t…
DescriptiveGraph GenerationScene Graph GenerationTransfer Learning+1Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation
Scene graph generation (SGG) has gained tremendous progress in recent years. However, its underlying long-tailed distribution of predicate classes is a challenging problem. For extremely unbalanced predicate distribution…
DiversityGraph GenerationMixture-of-Expertsobject-detection+3Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation
The Scene Graph Generation (SGG) task aims to detect all the objects and their pairwise visual relationships in a given image. Although SGG has achieved remarkable progress over the last few years, almost all existing SG…
Graph GenerationKnowledge DistillationObjectPredicate Classification+2Rethinking the Evaluation of Unbiased Scene Graph Generation
Current Scene Graph Generation (SGG) methods tend to predict frequent predicate categories and fail to recognize rare ones due to the severe imbalanced distribution of predicates. To improve the robustness of SGG models …
DiversityGraph GenerationScene Graph GenerationTriplet+1