Papers Video scene graph generation
“Video scene graph generation” 태그가 달린 논문 23편 · 필터 해제
SceneGraphVLM: Dynamic Scene Graph Generation from Video with Vision-Language Models
Scene graph generation provides a compact structured representation for visual perception, but accurate and fast graph prediction from images and videos remains challenging. Recent VLM-based methods can generate scene gr…
Video scene graph generationReinforcement LearningFrequency-guided Multi-level Reasoning for Scene Graph Generation in Video
Video Scene Graph Generation aims to obtain structured semantic representations of objects and their relationships in videos for high-level understanding. However, existing methods still have limitations in handling long…
Video scene graph generationRelation ClassificationRevisiting Weakly-Supervised Video Scene Graph Generation via Pair Affinity Learning
Weakly-supervised video scene graph generation (WS-VSGG) aims to parse video content into structured relational triplets without bounding box annotations and with only sparse temporal labeling, significantly reducing ann…
Video scene graph generationSynthetic Visual Genome 2: Extracting Large-scale Spatio-Temporal Scene Graphs from Videos
We introduce Synthetic Visual Genome 2 (SVG2), a large-scale panoptic video scene graph dataset. SVG2 contains over 636K videos with 6.6M objects, 52.0M attributes, and 6.7M relations, providing an order-of-magnitude inc…
Video scene graph generationVideo Question AnsweringPanoptic SegmentationSemantic ParsingClick2Graph: Interactive Panoptic Video Scene Graphs from a Single Click
State-of-the-art Video Scene Graph Generation (VSGG) systems provide structured visual understanding but operate as closed, feed-forward pipelines with no ability to incorporate human guidance. In contrast, promptable se…
Video scene graph generationRelational ReasoningScene UnderstandingUNO: Unifying One-stage Video Scene Graph Generation via Object-Centric Visual Representation Learning
Video Scene Graph Generation (VidSGG) aims to represent dynamic visual content by detecting objects and modeling their temporal interactions as structured graphs. Prior studies typically target either coarse-grained box-…
Video scene graph generationRepresentation LearningTHYME: Temporal Hierarchical-Cyclic Interactivity Modeling for Video Scene Graphs in Aerial Footage
The rapid proliferation of video in applications such as autonomous driving, surveillance, and sports analytics necessitates robust methods for dynamic scene understanding. Despite advances in static scene graph generati…
Video scene graph generationScene UnderstandingAutonomous DrivingHi-Dyna Graph: Hierarchical Dynamic Scene Graph for Robotic Autonomy in Human-Centric Environments
Autonomous operation of service robotics in human-centric scenes remains challenging due to the need for understanding of changing environments and context-aware decision-making. While existing approaches like topologica…
Graph GenerationHuman-Object Interaction DetectionNeRFScene Graph Generation+1SAMJAM: Zero-Shot Video Scene Graph Generation for Egocentric Kitchen Videos
Video Scene Graph Generation (VidSGG) is an important topic in understanding dynamic kitchen environments. Current models for VidSGG require extensive training to produce scene graphs. Recently, Vision Language Models (V…
Graph GenerationObjectScene Graph GenerationVideo scene graph generationDIFFVSGG: Diffusion-Driven Online Video Scene Graph Generation
Top-leading solutions for Video Scene Graph Generation (VSGG) typically adopt an offline pipeline. Though demonstrating promising performance, they remain unable to handle real-time video streams and consume large GPU me…
DenoisingGPUGraph GenerationScene Graph Generation+1Unbiased Video Scene Graph Generation via Visual and Semantic Dual Debiasing
Video Scene Graph Generation (VidSGG) aims to capture dynamic relationships among entities by sequentially analyzing video frames and integrating visual and semantic information. However, VidSGG is challenged by signific…
Graph GenerationScene Graph GenerationTripletVideo scene graph generationWeakly Supervised Video Scene Graph Generation via Natural Language Supervision
Existing Video Scene Graph Generation (VidSGG) studies are trained in a fully supervised manner, which requires all frames in a video to be annotated, thereby incurring high annotation cost compared to Image Scene Graph …
Graph GenerationImage CaptioningLarge Language ModelScene Graph Generation+1HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation
Multimodal LLMs have advanced vision-language tasks but still struggle with understanding video scenes. To bridge this gap, Video Scene Graph Generation (VidSGG) has emerged to capture multi-object relationships across v…
Graph GenerationQuestion AnsweringScene Graph GenerationVideo Captioning+2Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation
Spatio-Temporal Scene Graphs (STSGs) provide a concise and expressive representation of dynamic scenes by modelling objects and their evolving relationships over time. However, real-world visual relationships often exhib…
Graph GenerationScene Graph GenerationSpatio-temporal Scene GraphsVideo scene graph generationCYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos
Video scene graph generation (VidSGG) has emerged as a transformative approach to capturing and interpreting the intricate relationships among objects and their temporal dynamics in video sequences. In this paper, we int…
Graph GenerationScene Graph GenerationScene UnderstandingVideo scene graph generationSportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos
Video-based visual relation detection tasks, such as video scene graph generation, play important roles in fine-grained video understanding. However, current video visual relation detection datasets have two main limitat…
Graph GenerationRelationScene Graph GenerationVideo scene graph generation+2Panoptic 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+4HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos
Group Activity Scene Graph (GASG) generation is a challenging task in computer vision, aiming to anticipate and describe relationships between subjects and objects in video sequences. Traditional Video Scene Graph Genera…
Graph GenerationScene Graph GenerationScene UnderstandingVideo scene graph generationSpatial-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 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+2