Papers Scene Graph Generation
“Scene Graph Generation” 태그가 달린 논문 365편 · 필터 해제
Less is More: Toward Zero-Shot Local Scene Graph Generation via Foundation Models
Humans inherently recognize objects via selective visual perception, transform specific regions from the visual field into structured symbolic knowledge, and reason their relationships among regions based on the allocati…
Graph GenerationScene Graph GenerationAdaptive Visual Scene Understanding: Incremental Scene Graph Generation
Scene graph generation (SGG) analyzes images to extract meaningful information about objects and their relationships. In the dynamic visual world, it is crucial for AI systems to continuously detect new objects and estab…
BenchmarkingContinual LearningGraph Generationobject-detection+3Logical Bias Learning for Object Relation Prediction
Scene graph generation (SGG) aims to automatically map an image into a semantic structural graph for better scene understanding. It has attracted significant attention for its ability to provide object and relation infor…
Causal InferenceDecision MakingGraph GenerationObject+5Spatial-Temporal Knowledge-Embedded Transformer for Video Scene Graph Generation
Video scene graph generation (VidSGG) aims to identify objects in visual scenes and infer their relationships for a given video. It requires not only a comprehensive understanding of each object scattered on the whole sc…
Graph GenerationObjectScene Graph GenerationVideo scene graph generationPredicate 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 GenerationTowards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention
Many studies focus on improving pretraining or developing new backbones in text-video retrieval. However, existing methods may suffer from the learning and inference bias issue, as recent research suggests in other text-…
Action RecognitionGraph GenerationRetrievalScene Graph Generation+2STDG: Semi-Teacher-Student Training Paradigram for Depth-guided One-stage Scene Graph Generation
Scene Graph Generation is a critical enabler of environmental comprehension for autonomous robotic systems. Most of existing methods, however, are often thwarted by the intricate dynamics of background complexity, which …
Graph GenerationScene Graph GenerationZero-Shot Scene Graph Generation via Triplet Calibration and Reduction
Scene Graph Generation (SGG) plays a pivotal role in downstream vision-language tasks. Existing SGG methods typically suffer from poor compositional generalizations on unseen triplets. They are generally trained on incom…
Graph GenerationScene Graph GenerationTripletZero-Shot Scene Graph GenerationRepSGG: Novel Representations of Entities and Relationships for Scene Graph Generation
Scene Graph Generation (SGG) has achieved significant progress recently. However, most previous works rely heavily on fixed-size entity representations based on bounding box proposals, anchors, or learnable queries. As e…
Graph GenerationScene Graph GenerationHaystack: A Panoptic Scene Graph Dataset to Evaluate Rare Predicate Classes
Current scene graph datasets suffer from strong long-tail distributions of their predicate classes. Due to a very low number of some predicate classes in the test sets, no reliable metrics can be retrieved for the rarest…
Graph GenerationScene Graph GenerationTowards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic Grounding
Object proposal generation serves as a standard pre-processing step in Vision-Language (VL) tasks (image captioning, visual question answering, etc.). The performance of object proposals generated for VL tasks is current…
Graph GenerationImage CaptioningObjectObject Proposal Generation+3Head-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+2RLIPv2: Fast Scaling of Relational Language-Image Pre-training
Relational Language-Image Pre-training (RLIP) aims to align vision representations with relational texts, thereby advancing the capability of relational reasoning in computer vision tasks. However, hindered by the slow c…
Graph GenerationHuman-Object Interaction Detectionobject-detectionObject Detection+43D Scene Graph Prediction on Point Clouds Using Knowledge Graphs
3D scene graph prediction is a task that aims to concurrently predict object classes and their relationships within a 3D environment. As these environments are primarily designed by and for humans, incorporating commonse…
Graph GenerationKnowledge GraphsPredictionScene Graph GenerationCompositional 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+2Informative Scene Graph Generation via Debiasing
Scene graph generation aims to detect visual relationship triplets, (subject, predicate, object). Due to biases in data, current models tend to predict common predicates, e.g. "on" and "at", instead of informative ones, …
BlockingGraph GenerationImage CaptioningRetrieval+2Local-Global Information Interaction Debiasing for Dynamic Scene Graph Generation
The task of dynamic scene graph generation (DynSGG) aims to generate scene graphs for given videos, which involves modeling the spatial-temporal information in the video. However, due to the long-tailed distribution of s…
Graph GenerationMulti-Task LearningScene Graph GenerationGeneralized 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 GenerationEnvironment-Invariant Curriculum Relation Learning for Fine-Grained Scene Graph Generation
The scene graph generation (SGG) task is designed to identify the predicates based on the subject-object pairs.However,existing datasets generally include two imbalance cases: one is the class imbalance from the predicte…
Graph GenerationObjectRelationScene Graph Generation