4 citations · 8 across the 5 of their papers we have counts for
5 papers
TwinLiteNet+: An Enhanced Multi-Task Segmentation Model for Autonomous Driving
Quang-Huy Che, Duc-Tri Le, Minh-Quan Pham +2
Semantic segmentation is a fundamental perception task in autonomous driving, particularly for identifying drivable areas and lane markings to enable safe navigation. However, most…
TwinLiteNet: An Efficient and Lightweight Model for Driveable Area and Lane Segmentation in Self-Driving Cars
Quang Huy Che, Dinh Phuc Nguyen, Minh Quan Pham +1
Semantic segmentation is a common task in autonomous driving to understand the surrounding environment. Driveable Area Segmentation and Lane Detection are particularly important fo…
SHREC 2022: pothole and crack detection in the road pavement using images and RGB-D data
Elia Moscoso Thompson, Andrea Ranieri, Silvia Biasotti +6
This paper describes the methods submitted for evaluation to the SHREC 2022 track on pothole and crack detection in the road pavement. A total of 7 different runs for the semantic…
Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors
Naser Damer, César Augusto Fontanillo López, Meiling Fang +3
The main question this work aims at answering is: "can morphing attack detection (MAD) solutions be successfully developed based on synthetic data?". Towards that, this work introd…
Harnessing Geometric Constraints from Emotion Labels to improve Face Verification
Anand Ramakrishnan, Minh Pham, Jacob Whitehill
For the task of face verification, we explore the utility of harnessing auxiliary facial emotion labels to impose explicit geometric constraints on the embedding space when trainin…