1 citations · 1 across the 3 of their papers we have counts for
4 papers
MarsRecon: Self-Supervised and Multimodal Surface Representations for Mars
Akshay Naik, Marius F. R. Juston, Jay Mahajan
High-resolution orbital imagery offers a rich record of the Martian surface, but sparse geological labels limit supervised representation learning. We present MarsRecon, a geospati…
ReaDiT Guidance: Control for Image and Video Generation using Diffusion Transformer Features
Jay Mahajan, Chang Liu, Rauf Makharov +3
We present DiT Readout (ReaDiT) Guidance, a lightweight framework for controlling generation with Diffusion Transformer (DiT) models via their internal feature representations. Rea…
MineObserver 2.0: A Deep Learning & In-Game Framework for Assessing Natural Language Descriptions of Minecraft Imagery
Jay Mahajan, Samuel Hum, Jack Henhapl +5
MineObserver 2.0 is an AI framework that uses Computer Vision and Natural Language Processing for assessing the accuracy of learner-generated descriptions of Minecraft images that…
Street TryOn: Learning In-the-Wild Virtual Try-On from Unpaired Person Images
Aiyu Cui, Jay Mahajan, Viraj Shah +3
Most virtual try-on research is motivated to serve the fashion business by generating images to demonstrate garments on studio models at a lower cost. However, virtual try-on shoul…