6 papers
Quality-Aware Multimodal Fusion Reveals Implicit Identity in Valence-Arousal Features
Jisu Kim, Benjamin S. Riggan
Conventional face recognition relies on static appearance cues and degrades in unconstrained settings with expression variation, occlusion, and poor lighting. We hypothesize that a…
WeedExpert-R1: Incentivizing Botanical Reasoning in MLLMs with Reinforcement Learning for Precision Weed Grounding
Zonglin Yang, Wei-Zhen Liang, Nevin Lawrence +4
Precision weed control requires species-level identification and instance-level localization. However, conventional object detectors use a closed vocabulary, limiting their deploym…
Discovering EV Charging Site Archetypes Through Few Shot Forecasting: The First U.S.-Wide Study
Kshitij Nikhal, Lucas Ackerknecht, Benjamin S. Riggan +1
The decarbonization of transportation relies on the widespread adoption of electric vehicles (EVs), which requires an accurate understanding of charging behavior to ensure cost-eff…
Using Cross-Domain Detection Loss to Infer Multi-Scale Information for Improved Tiny Head Tracking
Jisu Kim, Alex Mattingly, Eung-Joo Lee +1
Head detection and tracking are essential for downstream tasks, but current methods often require large computational budgets, which increase latencies and ties up resources (e.g.,…
2D-3D Attention and Entropy for Pose Robust 2D Facial Recognition
J. Brennan Peace, Shuowen Hu, Benjamin S. Riggan
Despite recent advances in facial recognition, there remains a fundamental issue concerning degradations in performance due to substantial perspective (pose) differences between en…
Cross-Spectral Attention for Unsupervised RGB-IR Face Verification and Person Re-identification
Kshitij Nikhal, Cedric Nimpa Fondje, Benjamin S. Riggan
Cross-spectral biometrics, such as matching imagery of faces or persons from visible (RGB) and infrared (IR) bands, have rapidly advanced over the last decade due to increasing sen…