3 papers
cs.CV2026
Does Your VFM Speak Plant? The Botanical Grammar of Vision Foundation Models for Object Detection
Lars Lundqvist, Earl Ranario, Hamid Kamangir +4
Vision foundation models (VFMs) offer the promise of zero-shot object detection without task-specific training data, yet their performance in complex agricultural scenes remains hi…
cs.CV2026
A Vision Language Model for Generating Procedural Plant Architecture Representations from Simulated Images
Heesup Yun, Isaac Kazuo Uyehara, Ioannis Droutsas +4
Three-dimensional (3D) procedural plant architecture models have emerged as an important tool for simulation-based studies of plant structure and function, extracting plant archite…
cs.CV2026
Using Vision Language Foundation Models to Generate Plant Simulation Configurations via In-Context Learning
Heesup Yun, Isaac Kazuo Uyehara, Earl Ranario +4
This paper introduces a synthetic benchmark to evaluate the performance of vision language models (VLMs) in generating plant simulation configurations for digital twins. While func…