Search Results for author:
Found 8 papers, 5 papers with code
CrackNex: a Few-shot Low-light Crack Segmentation Model Based on Retinex Theory for UAV Inspections
LCSD consists of 102 well-illuminated crack images and 41 low-light crack images.
GRIP: Graph-based Interaction-aware Trajectory Prediction
The prediction error of GRIP is one meter shorter than existing schemes.
GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving
Despite the advancement in the technology of autonomous driving cars, the safety of a self-driving car is still a challenging problem that has not been well studied.
DAC: Data-free Automatic Acceleration of Convolutional Networks
A complex deep learning model with high accuracy runs slowly on resource-limited devices, while a light-weight model that runs much faster loses accuracy.
Recurrent Neural Networks based Obesity Status Prediction Using Activity Data
Obesity is a serious public health concern world-wide, which increases the risk of many diseases, including hypertension, stroke, and type 2 diabetes.
ReHAR: Robust and Efficient Human Activity Recognition
The whole model is trained end-to-end to allow meaningful representations to be generated for the final activity recognition.
SBGAR: Semantics Based Group Activity Recognition
Activity recognition has become an important function in many emerging computer vision applications e. g. automatic video surveillance system, human-computer interaction application, and video recommendation system, etc.
Category-Blind Human Action Recognition: A Practical Recognition System
In this paper, we propose the category-blind human recognition method (CHARM) which can recognize a human action without making assumptions of the action category.
