Papers Panoptic Scene Graph Generation
“Panoptic Scene Graph Generation” 태그가 달린 논문 23편 · 필터 해제
T-STAR: A Large-Scale Benchmark for Spatio-Temporal Panoptic Scene Graph Generation in Satellite Video
Structured understanding of satellite video is essential for advancing dynamic geospatial scene analysis from low-level perception to high-level cognition. To move beyond object-centric perception, this paper introduces …
Panoptic Scene Graph GenerationDSFlash: Comprehensive Panoptic Scene Graph Generation in Realtime
Scene Graph Generation (SGG) aims to extract a detailed graph structure from an image, a representation that holds significant promise as a robust intermediate step for complex downstream tasks like reasoning for embodie…
Panoptic Scene Graph GenerationSPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning
Panoptic Scene Graph Generation (PSG) integrates instance segmentation with relation understanding to capture pixel-level structural relationships in complex scenes. Although recent approaches leveraging pre-trained visi…
DenoisingGraph GenerationInstance SegmentationPanoptic Scene Graph Generation+4Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene
The latest emerged 4D Panoptic Scene Graph (4D-PSG) provides an advanced-ever representation for comprehensively modeling the dynamic 4D visual real world. Unfortunately, current pioneering 4D-PSG research can largel…
Graph GenerationLarge Language ModelPanoptic Scene Graph GenerationScene Graph Generation+1Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation
Federated learning (FL) has recently garnered attention as a data-decentralized training framework that enables the learning of deep models from locally distributed samples while keeping data privacy. Built upon the fram…
BenchmarkingFederated LearningGraph GenerationPanoptic Scene Graph Generation+1Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation
To equip artificial intelligence with a comprehensive understanding towards a temporal world, video and 4D panoptic scene graph generation abstracts visual data into nodes to represent entities and edges to capture tempo…
Contrastive LearningGraph GenerationPanoptic Scene Graph GenerationRelation+2OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal Models
Panoptic Scene Graph Generation (PSG) aims to segment objects and recognize their relations, enabling the structured understanding of an image. Previous methods focus on predicting predefined object and relation categori…
Graph Generationobject-detectionObject DetectionPanoptic Scene Graph Generation+5From Easy to Hard: Learning Curricular Shape-aware Features for Robust Panoptic Scene Graph Generation
Panoptic Scene Graph Generation (PSG) aims to generate a comprehensive graph-structure representation based on panoptic segmentation masks. Despite remarkable progress in PSG, almost all existing methods neglect the impo…
Graph GenerationKnowledge DistillationPanoptic Scene Graph GenerationPanoptic Segmentation+1A Fair Ranking and New Model for Panoptic Scene Graph Generation
In panoptic scene graph generation (PSGG), models retrieve interactions between objects in an image which are grounded by panoptic segmentation masks. Previous evaluations on panoptic scene graphs have been subject to an…
Graph GenerationPanoptic Scene Graph GenerationPanoptic SegmentationScene Graph Generation4D Panoptic Scene Graph Generation
We are living in a three-dimensional space while moving forward through a fourth dimension: time. To allow artificial intelligence to develop a comprehensive understanding of such a 4D environment, we introduce 4D Panopt…
4D Panoptic SegmentationGraph GenerationLanguage ModellingLarge Language Model+4DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation
Scene graph generation aims to capture detailed spatial and semantic relationships between objects in an image, which is challenging due to incomplete labelling, long-tailed relationship categories, and relational semant…
Graph GenerationGraph MatchingPanoptic Scene Graph GenerationRelation+2Contextual Associated Triplet Queries for Panoptic Scene Graph Generation
The Panoptic Scene Graph generation (PSG) task aims to extract the triplets composed of subject, object, and relation based on panoptic segmentation. For one-stage methods, PSGTR predicts the subject, object, and relatio…
Graph GenerationObjectPanoptic Scene Graph GenerationPanoptic Segmentation+3Panoptic Video Scene Graph Generation
Towards building comprehensive real-world visual perception systems, we propose and study a new problem called panoptic scene graph generation (PVSG). PVSG relates to the existing video scene graph generation (VidSGG) pr…
Graph GenerationPanoptic Scene Graph GenerationPanoptic SegmentationScene Graph Generation+4VLPrompt: Vision-Language Prompting for Panoptic Scene Graph Generation
Panoptic Scene Graph Generation (PSG) aims at achieving a comprehensive image understanding by simultaneously segmenting objects and predicting relations among objects. However, the long-tail problem among relations lead…
Graph GenerationPanoptic Scene Graph GenerationRelationRelation Prediction+1TextPSG: Panoptic Scene Graph Generation from Textual Descriptions
Panoptic Scene Graph has recently been proposed for comprehensive scene understanding. However, previous works adopt a fully-supervised learning manner, requiring large amounts of pixel-wise densely-annotated data, which…
Graph GenerationPanoptic Scene Graph GenerationScene Graph GenerationScene UnderstandingDomain-wise Invariant Learning for Panoptic Scene Graph Generation
Panoptic Scene Graph Generation (PSG) involves the detection of objects and the prediction of their corresponding relationships (predicates). However, the presence of biased predicate annotations poses a significant chal…
Graph GenerationPanoptic Scene Graph GenerationScene Graph GenerationPanoptic Scene Graph Generation with Semantics-Prototype Learning
Panoptic Scene Graph Generation (PSG) parses objects and predicts their relationships (predicate) to connect human language and visual scenes. However, different language preferences of annotators and semantic overlaps b…
Graph GenerationPanoptic Scene Graph GenerationScene Graph GenerationPair then Relation: Pair-Net for Panoptic Scene Graph Generation
Panoptic Scene Graph (PSG) is a challenging task in Scene Graph Generation (SGG) that aims to create a more comprehensive scene graph representation using panoptic segmentation instead of boxes. Compared to SGG, PSG has …
Graph GenerationPanoptic Scene Graph GenerationPanoptic SegmentationRelation+1HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph Generation
Panoptic Scene Graph generation (PSG) is a recently proposed task in image scene understanding that aims to segment the image and extract triplets of subjects, objects and their relations to build a scene graph. This tas…
Panoptic Scene Graph GenerationScene Graph GenerationScene UnderstandingPanoptic Scene Graph Generation
Existing research addresses scene graph generation (SGG) -- a critical technology for scene understanding in images -- from a detection perspective, i.e., objects are detected using bounding boxes followed by prediction …
BenchmarkingPanoptic Scene Graph GenerationScene Graph GenerationScene Understanding