In the latest in our series of interviews meeting the AAAI/SIGAI Doctoral Consortium participants, we caught up with Aniket Roy to find out more about his research on generative models for computer vision tasks. Tell us a bit about your PhD - where did you study, and what was the topic of your research? I recently completed my PhD in Computer Science at Johns Hopkins University, where I worked under the supervision of Bloomberg Distinguished Professor Rama Chellappa. My research primarily focused on developing methods for resource-constrained image generation and visual understanding. In particular, I explored how modern generative models can be adapted to operate efficiently while maintaining strong performance.

Our experiments demonstrate that MSVMamba is highly competitive, with the MSVMamba-Tinymodel achieving83.0%

As aresult, there is aproliferation of distinct architectures and loss functions for different vision tasks.

Recently, another type of networks with stacked Transformer blocks emerged.