66 citations · 97 across the 15 of their papers we have counts for
5 papers · 1 filter
mmAnomaly: Leveraging Visual Context for Robust Anomaly Detection in the Non-Visual World with mmWave Radar
Tarik Reza Toha, Shao-Jung, Lu +2
mmWave radar enables human sensing in non-visual scenarios-e.g., through clothing or certain types of walls-where traditional cameras fail due to occlusion or privacy limitations.…
mmCounter: Static People Counting in Dense Indoor Scenarios Using mmWave Radar
Tarik Reza Toha, Shao-Jung, Lu +1
mmWave radars struggle to detect or count individuals in dense, static (non-moving) groups due to limitations in spatial resolution and reliance on movement for detection. We prese…
mmWEAVER: Environment-Specific mmWave Signal Synthesis from a Photo and Activity Description
Mahathir Monjur, Shahriar Nirjon
Realistic signal generation and dataset augmentation are essential for advancing mmWave radar applications such as activity recognition and pose estimation, which rely heavily on d…
mmJoints: Expanding Joint Representations Beyond (x,y,z) in mmWave-Based 3D Pose Estimation
Zhenyu Wang, Mahathir Monjur, Shahriar Nirjon
In mmWave-based pose estimation, sparse signals and weak reflections often cause models to infer body joints from statistical priors rather than sensor data. While prior knowledge…
Characterizing Disparity Between Edge Models and High-Accuracy Base Models for Vision Tasks
Zhenyu Wang, Shahriar Nirjon
Edge devices, with their widely varying capabilities, support a diverse range of edge AI models. This raises the question: how does an edge model differ from a high-accuracy (base)…