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The proposed EdgeNet takes the features map of the last layer of the detector's backbone as input and outputs a (fixed-size) set of relevant edges. A sparse unlabeled graph is obtained by associating the predicted edges with the localized objects via the linear assignment process (Hungarian matching algorithm).
Scene graph captures rich semantic information of an image by representing objects and their relationships as nodes and edges of a graph.
A novel module named EdgeNet is proposed that directly predicts the set of relevant edges and helps to prune out a significant number of unrelated object ...
A method is presented for the automatic identification and extraction of feature information from the solid model of an object. The procedure consists in ...
Bibliographic details on EdgeNet for efficient scene graph classification.
EdgeNet for efficient scene graph classification. B.S. Vivek 1. ,. JAYAVARDHANA GUBBI 1. ,. M.A. Rajan 1. ,. P. Balamuralidhar 1. ,. Arpan Pal 1. Show full list ...
Abstract: Scene graph captures rich semantic information of an image by representing objects and their relationships as nodes and edges of a graph. Recent works ...
Nov 8, 2024 · Bridging Knowledge Graphs to Generate Scene Graphs. Alireza ... EdgeNet for efficient scene graph classification. Vivek B.S ... Arpan ...
Given input images, scene graph generation (SGG) aims to produce comprehensive, graphical representations describing visual relationships among salient objects.
Missing: EdgeNet | Show results with:EdgeNet
A fully convolutional scene graph generation (FCSGG) model that detects objects and relations simultaneously and achieves highly competitive results on ...
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