86 citations · 104 across the 6 of their papers we have counts for
5 papers · 1 filter
GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR
Bharat Singh, Viveka Kulharia, Luyu Yang +3
Multimodal synthetic data generation is crucial in domains such as autonomous driving, robotics, augmented/virtual reality, and retail. We propose a novel approach, GenMM, for join…
A Revised Generative Evaluation of Visual Dialogue
Daniela Massiceti, Viveka Kulharia, Puneet K. Dokania +2
Evaluating Visual Dialogue, the task of answering a sequence of questions relating to a visual input, remains an open research challenge. The current evaluation scheme of the VisDi…
Multi-Agent Diverse Generative Adversarial Networks
Arnab Ghosh, Viveka Kulharia, Vinay Namboodiri +2
We propose MAD-GAN, an intuitive generalization to the Generative Adversarial Networks (GANs) and its conditional variants to address the well known problem of mode collapse. First…
Message Passing Multi-Agent GANs
Arnab Ghosh, Viveka Kulharia, Vinay Namboodiri
Communicating and sharing intelligence among agents is an important facet of achieving Artificial General Intelligence. As a first step towards this challenge, we introduce a novel…
Contextual RNN-GANs for Abstract Reasoning Diagram Generation
Arnab Ghosh, Viveka Kulharia, Amitabha Mukerjee +2
Understanding, predicting, and generating object motions and transformations is a core problem in artificial intelligence. Modeling sequences of evolving images may provide better…