1 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
JEDI: JEPA-to-Edge Distillation for Efficient Cropland Segmentation from Satellite Imagery
Kishor Kumar Bhaumik, Nicolas Roque dos Santos, Jia Chen +1
Large vision models provide useful representations for remote-sensing segmentation but are often too expensive for deployment at the satellite or field edge. Existing feature-level…
PerceptionBench: Evaluating Atomic Visual Perception in Multimodal Large Language Models
Zichao Lin, Yifeng Xie, Bowen Qu +30
We introduce PerceptionBench, a benchmark specifically designed to evaluate the atomic visual perception capabilities of Multimodal Large Language Models (MLLMs). Existing benchmar…
AD-SAM: Adapting the Segment Anything Model for Semantic Segmentation in Autonomous Driving
Mario Camarena, Het Patel, Fatemeh Nazari +3
This paper presents the Autonomous Driving Segment Anything Model (AD-SAM), a foundation-model adaptation framework for semantic segmentation in autonomous driving. AD-SAM combines…
Can SAM recognize crops? Quantifying the zero-shot performance of a semantic segmentation foundation model on generating crop-type maps using satellite imagery for precision agriculture
Rutuja Gurav, Het Patel, Zhuocheng Shang +4
Climate change is increasingly disrupting worldwide agriculture, making global food production less reliable. To tackle the growing challenges in feeding the planet, cutting-edge m…