Vivek B.S.

Papers

Total Citations

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About

Vivek B.S. is a computer vision researcher whose work focuses on scene graph generation and semantic scene understanding. His most-cited paper, “EdgeNet for efficient scene graph classification” (2022), addresses a fundamental challenge in visual reasoning: capturing the rich semantic relationships between objects in an image. By representing objects and their interactions as nodes and edges of a graph, his approach enhances how machines interpret complex visual scenes—a capability critical for tasks like image retrieval and action recognition. While his citation count is still growing, Vivek’s research contributes to a rapidly advancing area where efficient graph-based models are key to bridging the gap between raw pixels and high-level scene comprehension. His work stands at the intersection of deep learning and structured prediction, offering practical solutions for making scene graph classification more computationally feasible. For students and researchers exploring visual relationship modeling, Vivek’s research provides a solid foundation for understanding how graphs can unlock deeper semantic insights from images.