publications

2024

1. 

   Learning to Produce Semi-dense Correspondences for Visual Localization (Oral, top 3.3% (90/2719) of accepted papers)

   Khang Truong Giang, Soohwan Song^, and Sungho Jo^

   In Computer Vision and Pattern Recognition Conference (CVPR) 2024

   PDF Code

2023

1. RA-L

   HybGrasp: A Hybrid Learning-to-Adapt Architecture for Efficient Robot Grasping

   Jungwook Mun, Truong Khang, Yunghee Lee, Nayoung Oh, Sejoon Huh, Min Kim, and Sungho Jo

   IEEE Robotics and Automation Letters 2023
2. 

   TopicFM: Robust and Interpretable Topic-assisted Feature Matching

   Khang Truong Giang, Soohwan Song^, and Sungho Jo^

   In Proceedings of the AAAI conference on artificial intelligence 2023

   PDF Code
3. 

   Prior Depth-Based Multi-View Stereo Network for Online 3D Model Reconstruction

   Soohwan Song*, Khang Truong Giang*, Daekyum Kim, and Sungho Jo

   Pattern Recognition 2023

   PDF Code

2022

1. 

   CURVATURE-GUIDED DYNAMIC SCALE NETWORKS FOR MULTI-VIEW STEREO

   Khang Truong Giang, Soohwan Song, and Sungho Jo

   In International Conference on Learning Representations 2022

   PDF Code
2. JISE

   Revisiting Supervised Word Embeddings.

   Dieu Vu, Khang Truong, Khanh Nguyen, Ngo Van Linh, and Khoat Than

   Journal of Information Science & Engineering 2022

   Bib

   @article{vu2022revisiting,
     title = {Revisiting Supervised Word Embeddings.},
     author = {Dieu, Vu and Khang, Truong and Khanh, Nguyen and Ngo, Van Linh and Khoat, Than},
     journal = {Journal of Information Science \& Engineering},
     volume = {38},
     number = {2},
     year = {2022}
   }

2021

2020

1. 

   Sequential Depth Completion With Confidence Estimation for 3D Model Reconstruction

   Khang Truong Giang*, Soohwan Song*, Daekyum Kim, and Sunghee Choi

   IEEE Robotics and Automation Letters 2020

   PDF Code

2019

1. SPIE

   How to make a machine learn continuously: a tutorial of the Bayesian approach

   Khoat Than, Xuan Bui, Tung Nguyen-Trong, Khang Truong, Son Nguyen, Bach Tran, Ngo Van Linh, and Anh Nguyen-Duc

   Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications 2019

   Bib

   @article{than2019make,
     title = {How to make a machine learn continuously: a tutorial of the Bayesian approach},
     author = {Khoat, Than and Xuan, Bui and Tung, Nguyen-Trong and Khang, Truong and Son, Nguyen and Bach, Tran and Ngo, Van Linh and Anh, Nguyen-Duc},
     journal = {Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications},
     volume = {11006},
     pages = {163--170},
     year = {2019},
     publisher = {SPIE}
   }