34 citations · 127 across the 17 of their papers we have counts for
21 papers · 1 filter
UTOPIA: Unconstrained Tracking Objects without Preliminary Examination via Cross-Domain Adaptation
Pha Nguyen, Kha Gia Quach, John Gauch +3
Multiple Object Tracking (MOT) aims to find bounding boxes and identities of targeted objects in consecutive video frames. While fully-supervised MOT methods have achieved high acc…
Type-to-Track: Retrieve Any Object via Prompt-based Tracking
Pha Nguyen, Kha Gia Quach, Kris Kitani +1
One of the recent trends in vision problems is to use natural language captions to describe the objects of interest. This approach can overcome some limitations of traditional meth…
Multi-Camera Multi-Object Tracking on the Move via Single-Stage Global Association Approach
Pha Nguyen, Kha Gia Quach, Chi Nhan Duong +3
The development of autonomous vehicles generates a tremendous demand for a low-cost solution with a complete set of camera sensors capturing the environment around the car. It is e…
Depth Perspective-aware Multiple Object Tracking
Kha Gia Quach, Huu Le, Pha Nguyen +3
This paper aims to tackle Multiple Object Tracking (MOT), an important problem in computer vision but remains challenging due to many practical issues, especially occlusions. Indee…
Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles
Pha Nguyen, Kha Gia Quach, Chi Nhan Duong +3
The development of autonomous vehicles provides an opportunity to have a complete set of camera sensors capturing the environment around the car. Thus, it is important for object d…
DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking
Kha Gia Quach, Pha Nguyen, Huu Le +4
Multi-Camera Multiple Object Tracking (MC-MOT) is a significant computer vision problem due to its emerging applicability in several real-world applications. Despite a large number…
A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection & Segmentation
Ngan Le, Kashu Yamazaki, Dat Truong +2
In recent years, deep neural networks have achieved state-of-the-art performance in a variety of recognition and segmentation tasks in medical imaging including brain tumor segment…
LIAAD: Lightweight Attentive Angular Distillation for Large-scale Age-Invariant Face Recognition
Thanh-Dat Truong, Chi Nhan Duong, Kha Gia Quach +3
Disentangled representations have been commonly adopted to Age-invariant Face Recognition (AiFR) tasks. However, these methods have reached some limitations with (1) the requiremen…
Vec2Face: Unveil Human Faces from their Blackbox Features in Face Recognition
Chi Nhan Duong, Thanh-Dat Truong, Kha Gia Quach +3
Unveiling face images of a subject given his/her high-level representations extracted from a blackbox Face Recognition engine is extremely challenging. It is because the limitation…
ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks
Chi Nhan Duong, Khoa Luu, Kha Gia Quach +1
Large-scale face recognition in-the-wild has been recently achieved matured performance in many real work applications. However, such systems are built on GPU platforms and mostly…
Non-Volume Preserving-based Fusion to Group-Level Emotion Recognition on Crowd Videos
Kha Gia Quach, Ngan Le, Chi Nhan Duong +3
Group-level emotion recognition (ER) is a growing research area as the demands for assessing crowds of all sizes are becoming an interest in both the security arena as well as soci…
Automatic Face Aging in Videos via Deep Reinforcement Learning
Chi Nhan Duong, Khoa Luu, Kha Gia Quach +4
This paper presents a novel approach to synthesize automatically age-progressed facial images in video sequences using Deep Reinforcement Learning. The proposed method models facia…
MobiFace: A Lightweight Deep Learning Face Recognition on Mobile Devices
Chi Nhan Duong, Kha Gia Quach, Ibsa Jalata +2
Deep neural networks have been widely used in numerous computer vision applications, particularly in face recognition. However, deploying deep neural network face recognition on mo…
Longitudinal Face Aging in the Wild - Recent Deep Learning Approaches
Chi Nhan Duong, Khoa Luu, Kha Gia Quach +1
Face Aging has raised considerable attentions and interest from the computer vision community in recent years. Numerous approaches ranging from purely image processing techniques t…
Learning from Longitudinal Face Demonstration - Where Tractable Deep Modeling Meets Inverse Reinforcement Learning
Chi Nhan Duong, Kha Gia Quach, Khoa Luu +3
This paper presents a novel Subject-dependent Deep Aging Path (SDAP), which inherits the merits of both Generative Probabilistic Modeling and Inverse Reinforcement Learning to mode…
Deep Contextual Recurrent Residual Networks for Scene Labeling
T. Hoang Ngan Le, Chi Nhan Duong, Ligong Han +3
Designed as extremely deep architectures, deep residual networks which provide a rich visual representation and offer robust convergence behaviors have recently achieved exceptiona…
Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation
Ngan Le, Kha Gia Quach, Khoa Luu +2
Variational Level Set (LS) has been a widely used method in medical segmentation. However, it is limited when dealing with multi-instance objects in the real world. In addition, it…
Temporal Non-Volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition
Chi Nhan Duong, Kha Gia Quach, Khoa Luu +2
Modeling the long-term facial aging process is extremely challenging due to the presence of large and non-linear variations during the face development stages. In order to efficien…
Robust Deep Appearance Models
Kha Gia Quach, Chi Nhan Duong, Khoa Luu +1
This paper presents a novel Robust Deep Appearance Models to learn the non-linear correlation between shape and texture of face images. In this approach, two crucial components of…
Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling
Chi Nhan Duong, Khoa Luu, Kha Gia Quach +1
The "interpretation through synthesis" approach to analyze face images, particularly Active Appearance Models (AAMs) method, has become one of the most successful face modeling app…
Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines
Chi Nhan Duong, Khoa Luu, Kha Gia Quach +1
Modeling the face aging process is a challenging task due to large and non-linear variations present in different stages of face development. This paper presents a deep model appro…