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20162026
most citedContextual Symmetries in Probabilistic Graphical Models

5 citations · 8 across the 10 of their papers we have counts for

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cs.CV2026

Towards Spatio-Temporal World Scene Graph Generation from Monocular Videos

Rohith Peddi, Saurabh, Shravan Shanmugam +4

Spatio-temporal scene graphs provide a principled representation for modeling evolving object interactions, yet existing methods remain fundamentally frame-centric: they reason onl…

cs.CV2024

Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation

Rohith Peddi, Saurabh, Ayush Abhay Shrivastava +2

Spatio-Temporal Scene Graphs (STSGs) provide a concise and expressive representation of dynamic scenes by modeling objects and their evolving relationships over time. However, real…

cs.CV2019

MaskAAE: Latent space optimization for Adversarial Auto-Encoders

Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran +3

The field of neural generative models is dominated by the highly successful Generative Adversarial Networks (GANs) despite their challenges, such as training instability and mode c…

cs.CV2018

A Novel Technique for Evidence based Conditional Inference in Deep Neural Networks via Latent Feature Perturbation

Dinesh Khandelwal, Suyash Agrawal, Parag Singla +1

Auxiliary information can be exploited in machine learning models using the paradigm of evidence based conditional inference. Multi-modal techniques in Deep Neural Networks (DNNs)…

cs.CV2017

Coarse-to-Fine Lifted MAP Inference in Computer Vision

Haroun Habeeb, Ankit Anand, Mausam +1

There is a vast body of theoretical research on lifted inference in probabilistic graphical models (PGMs). However, few demonstrations exist where lifting is applied in conjunction…