4 citations · 7 across the 4 of their papers we have counts for
4 papers
Gradient-Guided Knowledge Distillation for Object Detectors
Qizhen Lan, Qing Tian
Deep learning models have demonstrated remarkable success in object detection, yet their complexity and computational intensity pose a barrier to deploying them in real-world appli…
Visual Saliency-Guided Channel Pruning for Deep Visual Detectors in Autonomous Driving
Jung Im Choi, Qing Tian
Deep neural network (DNN) pruning has become a de facto component for deploying on resource-constrained devices since it can reduce memory requirements and computation costs during…
TMHOI: Translational Model for Human-Object Interaction Detection
Lijing Zhu, Qizhen Lan, Alvaro Velasquez +4
Detecting human-object interactions (HOIs) is an intricate challenge in the field of computer vision. Existing methods for HOI detection heavily rely on appearance-based features,…
Comparison Of Deep Object Detectors On A New Vulnerable Pedestrian Dataset
Devansh Sharma, Tihitina Hade, Qing Tian
Pedestrian safety is one primary concern in autonomous driving. The under-representation of vulnerable groups in today's pedestrian datasets points to an urgent need for a dataset…