Search Results for author: Hyeongjin Kim

Found 2 papers, 0 papers with code

Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency

no code implementations21 May 2024 Hyeongjin Kim, Sangwon Kim, Dasom Ahn, Jong Taek Lee, Byoung Chul Ko

Scene graph generation (SGG) is an important task in image understanding because it represents the relationships between objects in an image as a graph structure, making it possible to understand the semantic relationships between objects intuitively.

Graph Generation Scene Graph Generation

Semantic Scene Graph Generation Based on an Edge Dual Scene Graph and Message Passing Neural Network

no code implementations2 Nov 2023 Hyeongjin Kim, Sangwon Kim, Jong Taek Lee, Byoung Chul Ko

Along with generative AI, interest in scene graph generation (SGG), which comprehensively captures the relationships and interactions between objects in an image and creates a structured graph-based representation, has significantly increased in recent years.

Graph Generation Relation +1

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