Search Results for author: Ngan Le

Found 53 papers, 25 papers with code

Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation

1 code implementation12 Apr 2017 Ngan Le, Kha Gia Quach, Khoa Luu, Marios Savvides, Chenchen Zhu

To address these issues and boost the classic variational LS methods to a new level of the learnable deep learning approaches, we propose a novel definition of contour evolution named Recurrent Level Set (RLS)} to employ Gated Recurrent Unit under the energy minimization of a variational LS functional.

Segmentation Semantic Segmentation

Automatic Face Aging in Videos via Deep Reinforcement Learning

no code implementations CVPR 2019 Chi Nhan Duong, Khoa Luu, Kha Gia Quach, Nghia Nguyen, Eric Patterson, Tien D. Bui, Ngan Le

This paper presents a novel approach to synthesize automatically age-progressed facial images in video sequences using Deep Reinforcement Learning.

Face Verification reinforcement-learning +1

MobiFace: A Lightweight Deep Learning Face Recognition on Mobile Devices

no code implementations27 Nov 2018 Chi Nhan Duong, Kha Gia Quach, Ibsa Jalata, Ngan Le, Khoa Luu

Deep neural networks have been widely used in numerous computer vision applications, particularly in face recognition.

Face Recognition

Non-Volume Preserving-based Fusion to Group-Level Emotion Recognition on Crowd Videos

no code implementations28 Nov 2018 Kha Gia Quach, Ngan Le, Chi Nhan Duong, Ibsa Jalata, Kaushik Roy, Khoa Luu

To demonstrate the robustness and effectiveness of each component in the proposed approach, three experiments were conducted: (i) evaluation on AffectNet database to benchmark the proposed EmoNet for recognizing facial expression; (ii) evaluation on EmotiW2018 to benchmark the proposed deep feature level fusion mechanism NVPF; and, (iii) examine the proposed TNVPF on an innovative Group-level Emotion on Crowd Videos (GECV) dataset composed of 627 videos collected from publicly available sources.

Emotion Recognition

Fast Flow Reconstruction via Robust Invertible nxn Convolution

no code implementations24 May 2019 Thanh-Dat Truong, Khoa Luu, Chi Nhan Duong, Ngan Le, Minh-Triet Tran

The experiments on CIFAR-10, ImageNet and Celeb-HQ datasets, have shown that our invertible $n \times n$ convolution helps to improve the performance of generative models significantly.

ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks

2 code implementations25 May 2019 Chi Nhan Duong, Khoa Luu, Kha Gia Quach, Ngan Le

In addition, this work introduces a novel Angular Distillation Loss for distilling the feature direction and the sample distributions of the teacher's hypersphere to its student.

Lightweight Face Recognition

Image Alignment in Unseen Domains via Domain Deep Generalization

no code implementations28 May 2019 Thanh-Dat Truong, Khoa Luu, Chi Nhan Duong, Ngan Le, Minh-Triet Tran

This paper presents a novel deep learning based approach to tackle the problem of across unseen modalities.

Domain Adaptation

LIAAD: Lightweight Attentive Angular Distillation for Large-scale Age-Invariant Face Recognition

no code implementations9 Apr 2020 Thanh-Dat Truong, Chi Nhan Duong, Kha Gia Quach, Ngan Le, Tien D. Bui, Khoa Luu

This work presents a novel Lightweight Attentive Angular Distillation (LIAAD) approach to Large-scale Lightweight AiFR that overcomes these limitations.

Age-Invariant Face Recognition

A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection & Segmentation

no code implementations3 Dec 2020 Ngan Le, Kashu Yamazaki, Dat Truong, Kha Gia Quach, Marios Savvides

The first objective is performed by our proposed contextual brain tumor detection network, which plays a role of an attention gate and focuses on the region around brain tumor only while ignoring the far neighbor background which is less correlated to the tumor.

Brain Tumor Segmentation Tumor Segmentation

Flow-based Deformation Guidance for Unpaired Multi-Contrast MRI Image-to-Image Translation

no code implementations3 Dec 2020 Toan Duc Bui, Manh Nguyen, Ngan Le, Khoa Luu

To capture temporal structures in the medical images, we explore the displacement between the consecutive slices using a deformation field.

Generative Adversarial Network Image-to-Image Translation +1

Agent-Environment Network for Temporal Action Proposal Generation

no code implementations17 Jul 2021 Viet-Khoa Vo-Ho, Ngan Le, Kashu Yamazaki, Akihiro Sugimoto, Minh-Triet Tran

Temporal action proposal generation is an essential and challenging task that aims at localizing temporal intervals containing human actions in untrimmed videos.

Temporal Action Proposal Generation

The Right to Talk: An Audio-Visual Transformer Approach

1 code implementation ICCV 2021 Thanh-Dat Truong, Chi Nhan Duong, The De Vu, Hoang Anh Pham, Bhiksha Raj, Ngan Le, Khoa Luu

Therefore, this work introduces a new Audio-Visual Transformer approach to the problem of localization and highlighting the main speaker in both audio and visual channels of a multi-speaker conversation video in the wild.

Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey

no code implementations25 Aug 2021 Ngan Le, Vidhiwar Singh Rathour, Kashu Yamazaki, Khoa Luu, Marios Savvides

In this work, we provide a detailed review of recent and state-of-the-art research advances of deep reinforcement learning in computer vision.

Image Segmentation object-detection +5

AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation

1 code implementation21 Oct 2021 Khoa Vo, Hyekang Joo, Kashu Yamazaki, Sang Truong, Kris Kitani, Minh-Triet Tran, Ngan Le

In this paper, we make an attempt to simulate that ability of a human by proposing Actor Environment Interaction (AEI) network to improve the video representation for temporal action proposals generation.

Action Detection Temporal Action Proposal Generation

SS-3DCapsNet: Self-supervised 3D Capsule Networks for Medical Segmentation on Less Labeled Data

no code implementations15 Jan 2022 Minh Tran, Loi Ly, Binh-Son Hua, Ngan Le

Capsule network is a recent new deep network architecture that has been applied successfully for medical image segmentation tasks.

Hippocampus Image Segmentation +4

Meta-Learning of NAS for Few-shot Learning in Medical Image Applications

no code implementations16 Mar 2022 Viet-Khoa Vo-Ho, Kashu Yamazaki, Hieu Hoang, Minh-Triet Tran, Ngan Le

To address such limitations, meta-learning has been adopted in the scenarios of few-shot learning and multiple tasks.

Few-Shot Learning Image Classification +1

3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation

2 code implementations16 Mar 2022 Tan Nguyen, Binh-Son Hua, Ngan Le

Medical image segmentation has been so far achieving promising results with Convolutional Neural Networks (CNNs).

Hippocampus Image Segmentation +3

Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation

1 code implementation16 Mar 2022 Ngoc-Vuong Ho, Tan Nguyen, Gia-Han Diep, Ngan Le, Binh-Son Hua

In this paper, we propose Point-Unet, a novel method that incorporates the efficiency of deep learning with 3D point clouds into volumetric segmentation.

Image Segmentation Medical Image Segmentation +2

ABN: Agent-Aware Boundary Networks for Temporal Action Proposal Generation

1 code implementation16 Mar 2022 Khoa Vo, Kashu Yamazaki, Sang Truong, Minh-Triet Tran, Akihiro Sugimoto, Ngan Le

Temporal action proposal generation (TAPG) aims to estimate temporal intervals of actions in untrimmed videos, which is a challenging yet plays an important role in many tasks of video analysis and understanding.

Action Detection Temporal Action Proposal Generation

Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles

no code implementations19 Apr 2022 Pha Nguyen, Kha Gia Quach, Chi Nhan Duong, Ngan Le, Xuan-Bac Nguyen, Khoa Luu

The experimental results on the nuScenes dataset demonstrate the benefits of the proposed method to produce SOTA performance on the existing vision-based tracking dataset.

3D Object Detection 3D Object Tracking +5

Self-supervised Domain Adaptation in Crowd Counting

no code implementations7 Jun 2022 Pha Nguyen, Thanh-Dat Truong, Miaoqing Huang, Yi Liang, Ngan Le, Khoa Luu

Self-training crowd counting has not been attentively explored though it is one of the important challenges in computer vision.

Crowd Counting Domain Adaptation

VLCap: Vision-Language with Contrastive Learning for Coherent Video Paragraph Captioning

1 code implementation26 Jun 2022 Kashu Yamazaki, Sang Truong, Khoa Vo, Michael Kidd, Chase Rainwater, Khoa Luu, Ngan Le

In this paper, we leverage the human perceiving process, that involves vision and language interaction, to generate a coherent paragraph description of untrimmed videos.

Contrastive Learning Video Captioning

Vec2Face-v2: Unveil Human Faces from their Blackbox Features via Attention-based Network in Face Recognition

no code implementations11 Sep 2022 Thanh-Dat Truong, Chi Nhan Duong, Ngan Le, Marios Savvides, Khoa Luu

We therefore introduce a new method named Attention-based Bijective Generative Adversarial Networks in a Distillation framework (DAB-GAN) to synthesize faces of a subject given his/her extracted face recognition features.

Face Recognition Face Reconstruction +2

Multimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised Learning

1 code implementation30 Sep 2022 Thinh Phan, Duc Le, Patel Brijesh, Donald Adjeroh, Jingxian Wu, Morten Olgaard Jensen, Ngan Le

Electrocardiogram (ECG) signal is one of the most effective sources of information mainly employed for the diagnosis and prediction of cardiovascular diseases (CVDs) connected with the abnormalities in heart rhythm.

ECG Classification Self-Knowledge Distillation +3

AOE-Net: Entities Interactions Modeling with Adaptive Attention Mechanism for Temporal Action Proposals Generation

1 code implementation5 Oct 2022 Khoa Vo, Sang Truong, Kashu Yamazaki, Bhiksha Raj, Minh-Triet Tran, Ngan Le

PMR module represents each video snippet by a visual-linguistic feature, in which main actors and surrounding environment are represented by visual information, whereas relevant objects are depicted by linguistic features through an image-text model.

Action Detection Temporal Action Proposal Generation

EmbryosFormer: Deformable Transformer and Collaborative Encoding-Decoding for Embryos Stage Development Classification

1 code implementation7 Oct 2022 Tien-Phat Nguyen, Trong-Thang Pham, Tri Nguyen, Hieu Le, Dung Nguyen, Hau Lam, Phong Nguyen, Jennifer Fowler, Minh-Triet Tran, Ngan Le

The transformer expanding path models the temporal coherency between embryo images to ensure monotonic non-decreasing constraint and is optimized by a segmentation head.

AISFormer: Amodal Instance Segmentation with Transformer

1 code implementation12 Oct 2022 Minh Tran, Khoa Vo, Kashu Yamazaki, Arthur Fernandes, Michael Kidd, Ngan Le

AISFormer explicitly models the complex coherence between occluder, visible, amodal, and invisible masks within an object's regions of interest by treating them as learnable queries.

Amodal Instance Segmentation Segmentation +1

Multi-Camera Multi-Object Tracking on the Move via Single-Stage Global Association Approach

no code implementations17 Nov 2022 Pha Nguyen, Kha Gia Quach, Chi Nhan Duong, Son Lam Phung, Ngan Le, Khoa Luu

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.

3D Object Detection Autonomous Vehicles +3

VLTinT: Visual-Linguistic Transformer-in-Transformer for Coherent Video Paragraph Captioning

1 code implementation28 Nov 2022 Kashu Yamazaki, Khoa Vo, Sang Truong, Bhiksha Raj, Ngan Le

Video paragraph captioning aims to generate a multi-sentence description of an untrimmed video with several temporal event locations in coherent storytelling.

Sentence Video Captioning

CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly Detection

1 code implementation9 Dec 2022 Hyekang Kevin Joo, Khoa Vo, Kashu Yamazaki, Ngan Le

Video anomaly detection (VAD) -- commonly formulated as a multiple-instance learning problem in a weakly-supervised manner due to its labor-intensive nature -- is a challenging problem in video surveillance where the frames of anomaly need to be localized in an untrimmed video.

Anomaly Detection Multiple Instance Learning +1

Contextual Explainable Video Representation: Human Perception-based Understanding

1 code implementation12 Dec 2022 Khoa Vo, Kashu Yamazaki, Phong X. Nguyen, Phat Nguyen, Khoa Luu, Ngan Le

We choose video paragraph captioning and temporal action detection to illustrate the effectiveness of human perception based-contextual representation in video understanding.

Action Detection Action Recognition +4

Open-Vocabulary Affordance Detection in 3D Point Clouds

1 code implementation4 Mar 2023 Toan Nguyen, Minh Nhat Vu, An Vuong, Dzung Nguyen, Thieu Vo, Ngan Le, Anh Nguyen

In this paper, we present the Open-Vocabulary Affordance Detection (OpenAD) method, which is capable of detecting an unbounded number of affordances in 3D point clouds.

Affordance Detection

FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding

1 code implementation CVPR 2023 Thanh-Dat Truong, Ngan Le, Bhiksha Raj, Jackson Cothren, Khoa Luu

Although Domain Adaptation in Semantic Scene Segmentation has shown impressive improvement in recent years, the fairness concerns in the domain adaptation have yet to be well defined and addressed.

Autonomous Driving Domain Adaptation +4

Translating Simulation Images to X-ray Images via Multi-Scale Semantic Matching

no code implementations16 Apr 2023 Jingxuan Kang, Tudor Jianu, Baoru Huang, Binod Bhattarai, Ngan Le, Frans Coenen, Anh Nguyen

In this paper, we propose a new method to translate simulation images from an endovascular simulator to X-ray images.

Image-to-Image Translation

AerialFormer: Multi-resolution Transformer for Aerial Image Segmentation

no code implementations12 Jun 2023 Kashu Yamazaki, Taisei Hanyu, Minh Tran, Adrian de Luis, Roy McCann, Haitao Liao, Chase Rainwater, Meredith Adkins, Jackson Cothren, Ngan Le

Aerial Image Segmentation is a top-down perspective semantic segmentation and has several challenging characteristics such as strong imbalance in the foreground-background distribution, complex background, intra-class heterogeneity, inter-class homogeneity, and tiny objects.

Image Segmentation Segmentation +1

MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation

2 code implementations6 Sep 2023 Nhat-Tan Bui, Dinh-Hieu Hoang, Quang-Thuc Nguyen, Minh-Triet Tran, Ngan Le

MEGANet is designed as an end-to-end framework, encompassing three key modules: an encoder, which is responsible for capturing and abstracting the features from the input image, a decoder, which focuses on salient features, and the Edge-Guided Attention module (EGA) that employs the Laplacian Operator to accentuate polyp boundaries.

Edge Detection Segmentation

SAM3D: Segment Anything Model in Volumetric Medical Images

2 code implementations7 Sep 2023 Nhat-Tan Bui, Dinh-Hieu Hoang, Minh-Triet Tran, Gianfranco Doretto, Donald Adjeroh, Brijesh Patel, Arabinda Choudhary, Ngan Le

Image segmentation remains a pivotal component in medical image analysis, aiding in the extraction of critical information for precise diagnostic practices.

Image Segmentation Segmentation +1

I-AI: A Controllable & Interpretable AI System for Decoding Radiologists' Intense Focus for Accurate CXR Diagnoses

1 code implementation24 Sep 2023 Trong Thang Pham, Jacob Brecheisen, Anh Nguyen, Hien Nguyen, Ngan Le

In the field of chest X-ray (CXR) diagnosis, existing works often focus solely on determining where a radiologist looks, typically through tasks such as detection, segmentation, or classification.

Language Modelling

Open-Fusion: Real-time Open-Vocabulary 3D Mapping and Queryable Scene Representation

no code implementations5 Oct 2023 Kashu Yamazaki, Taisei Hanyu, Khoa Vo, Thang Pham, Minh Tran, Gianfranco Doretto, Anh Nguyen, Ngan Le

Open-Fusion harnesses the power of a pre-trained vision-language foundation model (VLFM) for open-set semantic comprehension and employs the Truncated Signed Distance Function (TSDF) for swift 3D scene reconstruction.

3D Scene Reconstruction

SolarFormer: Multi-scale Transformer for Solar PV Profiling

no code implementations30 Oct 2023 Adrian de Luis, Minh Tran, Taisei Hanyu, Anh Tran, Liao Haitao, Roy McCann, Alan Mantooth, Ying Huang, Ngan Le

Accurate mapping of PV installations is crucial for understanding their adoption and informing energy policy.

WAVER: Writing-style Agnostic Text-Video Retrieval via Distilling Vision-Language Models Through Open-Vocabulary Knowledge

no code implementations15 Dec 2023 Huy Le, Tung Kieu, Anh Nguyen, Ngan Le

Text-video retrieval, a prominent sub-field within the domain of multimodal information retrieval, has witnessed remarkable growth in recent years.

Information Retrieval Knowledge Distillation +3

TSRNet: Simple Framework for Real-time ECG Anomaly Detection with Multimodal Time and Spectrogram Restoration Network

1 code implementation15 Dec 2023 Nhat-Tan Bui, Dinh-Hieu Hoang, Thinh Phan, Minh-Triet Tran, Brijesh Patel, Donald Adjeroh, Ngan Le

As a result, we introduce a specialized network called the Multimodal Time and Spectrogram Restoration Network (TSRNet) designed specifically for detecting anomalies in ECG signals.

Anomaly Detection Time Series

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