5 citations · 13 across the 8 of their papers we have counts for
8 papers
Subtle Signals: Video-based Detection of Infant Non-nutritive Sucking as a Neurodevelopmental Cue
Shaotong Zhu, Michael Wan, Sai Kumar Reddy Manne +2
Non-nutritive sucking (NNS), which refers to the act of sucking on a pacifier, finger, or similar object without nutrient intake, plays a crucial role in assessing healthy early de…
Automatic Infant Respiration Estimation from Video: A Deep Flow-based Algorithm and a Novel Public Benchmark
Sai Kumar Reddy Manne, Shaotong Zhu, Sarah Ostadabbas +1
Respiration is a critical vital sign for infants, and continuous respiratory monitoring is particularly important for newborns. However, neonates are sensitive and contact-based se…
Bridging the Domain Gap between Synthetic and Real-World Data for Autonomous Driving
Xiangyu Bai, Yedi Luo, Le Jiang +4
Modern autonomous systems require extensive testing to ensure reliability and build trust in ground vehicles. However, testing these systems in the real-world is challenging due to…
SPAC-Net: Synthetic Pose-aware Animal ControlNet for Enhanced Pose Estimation
Le Jiang, Sarah Ostadabbas
Animal pose estimation has become a crucial area of research, but the scarcity of annotated data is a significant challenge in developing accurate models. Synthetic data has emerge…
A Video-based End-to-end Pipeline for Non-nutritive Sucking Action Recognition and Segmentation in Young Infants
Shaotong Zhu, Michael Wan, Elaheh Hatamimajoumerd +10
We present an end-to-end computer vision pipeline to detect non-nutritive sucking (NNS) -- an infant sucking pattern with no nutrition delivered -- as a potential biomarker for dev…
Prior-Aware Synthetic Data to the Rescue: Animal Pose Estimation with Very Limited Real Data
Le Jiang, Shuangjun Liu, Xiangyu Bai +1
Accurately annotated image datasets are essential components for studying animal behaviors from their poses. Compared to the number of species we know and may exist, the existing l…