Behjat Siddiquie — accepted AI-conference papers

2023

LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation

Koutilya PNVR, Bharat Singh, Pallabi Ghosh, Behjat Siddiquie, David Jacobs

ICCV 2023oral

Large-scale pre-training tasks like image classification, captioning, or self-supervised techniques do not incentivize learning the semantic boundaries of objects. However, recent generative foundation models built using text-based latent diffusion techniques may learn semantic boundaries. This is b…

Cited by 38 PDF ↗code ↗Scholar ↗

2021

Energy-Based Learning for Scene Graph Generation

Mohammed Suhail, Abhay Mittal, Behjat Siddiquie, Chris Broaddus, Jayan Eledath, Gerard Medioni +1

CVPR 2021poster

Traditional scene graph generation methods are trained using cross-entropy losses that treat objects and relationships as independent entities. Such a formulation, however, ignores structure in the output space, in an inherently structured prediction problem. In this work, we introduce a novel energ…

Cited by 196 PDF ↗code ↗Scholar ↗