1 citations · 1 across the 7 of their papers we have counts for
8 papers
FeudalNav: A Simple Framework for Visual Navigation
Faith Johnson, Bryan Bo Cao, Shubham Jain +2
Visual navigation for robotics is inspired by the human ability to navigate environments using visual cues and memory, eliminating the need for detailed maps. In unseen, unmapped,…
Agtech Framework for Cranberry-Ripening Analysis Using Vision Foundation Models
Faith Johnson, Ryan Meegan, Jack Lowry +2
Agricultural domains are being transformed by recent advances in AI and computer vision that support quantitative visual evaluation. Using aerial and ground imaging over a time ser…
Memory Proxy Maps for Visual Navigation
Faith Johnson, Bryan Bo Cao, Ashwin Ashok +2
Visual navigation takes inspiration from humans, who navigate in previously unseen environments using vision without detailed environment maps. Inspired by this, we introduce a nov…
Improvements to SDXL in NovelAI Diffusion V3
Juan Ossa, Eren Doğan, Alex Birch +1
In this technical report, we document the changes we made to SDXL in the process of training NovelAI Diffusion V3, our state of the art anime image generation model.
A Landmark-Aware Visual Navigation Dataset
Faith Johnson, Bryan Bo Cao, Kristin Dana +2
Map representations learned by expert demonstrations have shown promising research value. However, the field of visual navigation still faces challenges due to the lack of real-wor…
Feudal Networks for Visual Navigation
Faith Johnson, Bryan Bo Cao, Ashwin Ashok +2
Visual navigation follows the intuition that humans can navigate without detailed maps. A common approach is interactive exploration while building a topological graph with images…
Hierarchical Reinforcement Learning for Temporal Pattern Prediction
Faith Johnson, Kristin Dana
In this work, we explore the use of hierarchical reinforcement learning (HRL) for the task of temporal sequence prediction. Using a combination of deep learning and HRL, we develop…
Vision-Based Cranberry Crop Ripening Assessment
Faith Johnson, Jack Lowry, Kristin Dana +1
Agricultural domains are being transformed by recent advances in AI and computer vision that support quantitative visual evaluation. Using drone imaging, we develop a framework for…