Perception and Intelligence Laboratory

Recent Publications

Position-aware Location Regression Network for Temporal Video Grounding (AVSS, 2021)

Detecting and Removing Text in the Wild (IEEE Access, 2021)

Rotation-Aware 3D Vehicle Detection From Point Cloud (IEEE Access, 2021)

Multi-modal Object Detection, Tracking, and Action Classification for Unmanned Outdoor Surveillance Robots (ICCAS, 2021)

Influence-balanced Loss for Imbalanced Visual Classification (ICCV, 2021)

Research

The goal of the PILab is to gain useful technologies on perception and intelligence which can be applied to visual surveillance systems, inspection machines, robots, etc.

We are developing perceptual primitives to detect, track, and recognize human/vehicles, faces and to understand abnormal behaviors and situations through visual information. In addition, we are developing incremental learning models including probabilistic learning machines for integrating multiple sensory modalities in the changing environments.

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