Papers Predicate Classification
“Predicate Classification” 태그가 달린 논문 22편 · 필터 해제
Situational Scene Graph for Structured Human-centric Situation Understanding
Graph based representation has been widely used in modelling spatio-temporal relationships in video understanding. Although effective, existing graph-based approaches focus on capturing the human-object relationships whi…
Graph GenerationPredicate ClassificationScene Graph GenerationVideo UnderstandingTD^2-Net: Toward Denoising and Debiasing for Dynamic Scene Graph Generation
Dynamic scene graph generation (SGG) focuses on detecting objects in a video and determining their pairwise relationships. Existing dynamic SGG methods usually suffer from several issues, including 1) Contextual noise, a…
DenoisingGraph GenerationObjectPredicate Classification+1RelVAE: Generative Pretraining for few-shot Visual Relationship Detection
Visual relations are complex, multimodal concepts that play an important role in the way humans perceive the world. As a result of their complexity, high-quality, diverse and large scale datasets for visual relations are…
Predicate ClassificationRelationship DetectionVisual Relationship DetectionEnhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge
This work introduces an enhanced approach to generating scene graphs by incorporating both a relationship hierarchy and commonsense knowledge. Specifically, we begin by proposing a hierarchical relation head that exploit…
Large Language ModelMultimodal Deep LearningPredicate ClassificationRelation+4Predicate Classification Using Optimal Transport Loss in Scene Graph Generation
In scene graph generation (SGG), learning with cross-entropy loss yields biased predictions owing to the severe imbalance in the distribution of the relationship labels in the dataset. Thus, this study proposes a method …
Graph GenerationPredicate ClassificationScene Graph GenerationHierarchical Relationships: A New Perspective to Enhance Scene Graph Generation
This paper presents a finding that leveraging the hierarchical structures among labels for relationships and objects can substantially improve the performance of scene graph generation systems. The focus of this work is …
Contrastive LearningGraph GenerationPredicate ClassificationScene Graph Generation1st Place Solution for PSG competition with ECCV'22 SenseHuman Workshop
Panoptic Scene Graph (PSG) generation aims to generate scene graph representations based on panoptic segmentation instead of rigid bounding boxes. Existing PSG methods utilize one-stage paradigm which simultaneously gene…
Multi-class ClassificationPanoptic SegmentationPredicate ClassificationRelation+4IS-GGT: Iterative Scene Graph Generation With Generative Transformers
Scene graphs provide a rich, structured representation of a scene by encoding the entities (objects) and their spatial relationships in a graphical format. This representation has proven useful in several tasks, such…
Graph GenerationLink Predictionobject-detectionObject Detection+3Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs
Graph neural networks have shown to learn effective node representations, enabling node-, link-, and graph-level inference. Conventional graph networks assume static relations between nodes, while relations between entit…
Graph Attentionobject-detectionObject DetectionPredicate ClassificationIterative Scene Graph Generation with Generative Transformers
Scene graphs provide a rich, structured representation of a scene by encoding the entities (objects) and their spatial relationships in a graphical format. This representation has proven useful in several tasks, such as …
Graph GenerationLink Predictionobject-detectionObject 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+2Fine-Grained Predicates Learning for Scene Graph Generation
The performance of current Scene Graph Generation models is severely hampered by some hard-to-distinguish predicates, e.g., "woman-on/standing on/walking on-beach" or "woman-near/looking at/in front of-child". While gene…
Fine-Grained Image ClassificationGraph Generationimage-classificationImage Classification+2Fine-Grained Scene Graph Generation with Data Transfer
Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images. Recent works have made a steady progress on SGG, and provide useful tools for high-level vision and language understand…
Graph GenerationPredicate ClassificationScene Graph ClassificationScene Graph Detection+2Biasing Like Human: A Cognitive Bias Framework for Scene Graph Generation
Scene graph generation is a sophisticated task because there is no specific recognition pattern (e.g., "looking at" and "near" have no conspicuous difference concerning vision, whereas "near" could occur between entities…
Graph GenerationPredicate ClassificationRelationScene Graph GenerationRelation Regularized Scene Graph Generation
Scene graph generation (SGG) is built on top of detected objects to predict object pairwise visual relations for describing the image content abstraction. Existing works have revealed that if the links between objects ar…
Graph ClassificationGraph GenerationObjectPredicate Classification+4PPDL: Predicate Probability Distribution Based Loss for Unbiased Scene Graph Generation
Scene Graph Generation (SGG) has attracted more and more attention from visual researchers in recent years, since Scene Graph (SG) is valuable in many downstream tasks due to its rich structural-semantic details. How…
Graph GenerationPredicate ClassificationScene Graph GenerationUnbiased Scene Graph GenerationClassification-Then-Grounding: Reformulating Video Scene Graphs as Temporal Bipartite Graphs
Today's VidSGG models are all proposal-based methods, i.e., they first generate numerous paired subject-object snippets as proposals, and then conduct predicate classification for each proposal. In this paper, we argue t…
Predicate ClassificationTackling the Challenges in Scene Graph Generation with Local-to-Global Interactions
In this work, we seek new insights into the underlying challenges of the Scene Graph Generation (SGG) task. Quantitative and qualitative analysis of the Visual Genome dataset implies -- 1) Ambiguity: even if inter-object…
Bidirectional Relationship ClassificationDiagnosticGraph GenerationObject+3Visual Distant Supervision for Scene Graph Generation
Scene graph generation aims to identify objects and their relations in images, providing structured image representations that can facilitate numerous applications in computer vision. However, scene graph models usually …
Graph GenerationPredicate ClassificationRelationScene Graph GenerationSceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks. This work proposes a method to incrementally build up semantic scene graphs from a 3D environment giv…
3D Object Classification3d scene graph generationGraph Neural NetworkPanoptic Segmentation+3