2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDARS-7.3
Paper Title CONTEXTUAL LABEL TRANSFORMATION FOR SCENE GRAPH GENERATION
Authors Wonhee Lee, Samsung Electronics, Republic of Korea; Sungeun Kim, Gunhee Kim, Seoul National University, Republic of Korea
SessionARS-7: Image and Video Interpretation and Understanding 2
LocationArea H
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Image and Video Analysis, Synthesis, and Retrieval: Image & Video Interpretation and Understanding
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract For scene graph generation, it is crucial to properly understand the relationships of objects within the context of the image. We design a label transformation method using a Transformer-VAE (Variational Autoencoder) structure, which converts bounding box labels into auxiliary labels that contain each object's context in an unsupervised manner. The auxiliary labels are then trained jointly with bounding box labels and relation labels in a multi-task way. Our approach does not require any external datasets or language prior and is applicable to any graph generation models that infer the relationship between pairs of objects. We validate our method's effectiveness and scalability with state-of-the-art scene graph generation models on VRD and VG datasets.