14 citations · 33 across the 6 of their papers we have counts for
4 papers · 2 filters
LCD: Learned Cross-Domain Descriptors for 2D-3D Matching
Quang-Hieu Pham, Mikaela Angelina Uy, Binh-Son Hua +3
In this work, we present a novel method to learn a local cross-domain descriptor for 2D image and 3D point cloud matching. Our proposed method is a dual auto-encoder neural network…
A*3D Dataset: Towards Autonomous Driving in Challenging Environments
Quang-Hieu Pham, Pierre Sevestre, Ramanpreet Singh Pahwa +6
With the increasing global popularity of self-driving cars, there is an immediate need for challenging real-world datasets for benchmarking and training various computer vision tas…
Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data
Mikaela Angelina Uy, Quang-Hieu Pham, Binh-Son Hua +2
Deep learning techniques for point cloud data have demonstrated great potentials in solving classical problems in 3D computer vision such as 3D object classification and segmentati…
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields
Quang-Hieu Pham, Duc Thanh Nguyen, Binh-Son Hua +2
Deep learning techniques have become the to-go models for most vision-related tasks on 2D images. However, their power has not been fully realised on several tasks in 3D space, e.g…