MineObserver 2.0: A Deep Learning & In-Game Framework for Assessing Natural Language Descriptions of Minecraft Imagery

no code implementations • 19 Dec 2023 • Jay Mahajan, Samuel Hum, Jack Henhapl, Diya Yunus, Matthew Gadbury, Emi Brown, Jeff Ginger, H. Chad Lane

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 include some scientifically relevant content.

Street TryOn: Learning In-the-Wild Virtual Try-On from Unpaired Person Images

1 code implementation • 27 Nov 2023 • Aiyu Cui, Jay Mahajan, Viraj Shah, Preeti Gomathinayagam, Chang Liu, Svetlana Lazebnik

By contrast, it is hard to collect paired data for in-the-wild scenes, and therefore, virtual try-on for casual images of people with more diverse poses against cluttered backgrounds is rarely studied.

Image Generation Semantic Segmentation +4