The Hong Kong University of Science and Technology

research

∙ 08/10/2021

Deep Metric Learning for Open World Semantic Segmentation

Classical close-set semantic segmentation networks have limited ability ...

Jun Cen, et al. ∙

research

∙ 01/24/2019

Deep Generative Learning via Variational Gradient Flow

We propose a general framework to learn deep generative models via Varia...

Gao Yuan, et al. ∙

research

∙ 09/01/2019

DeepHealth: Deep Learning for Health Informatics

Machine learning and deep learning have provided us with an exploration ...

Gloria Hyun-Jung Kwak, et al. ∙

research

∙ 12/24/2019

Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data

Humans are capable of learning a new behavior by observing others to per...

Boyi Liu, et al. ∙

research

∙ 11/11/2019

PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation

In this work, we present a novel data-driven method for robust 6DoF obje...

Yisheng He, et al. ∙

research

∙ 07/12/2022

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

Conventionally, Earth system (e.g., weather and climate) forecasting rel...

Zhihan Gao, et al. ∙

research

∙ 12/29/2018

SPI-Optimizer: an integral-Separated PI Controller for Stochastic Optimization

To overcome the oscillation problem in the classical momentum-based opti...

Dan Wang, et al. ∙

research

∙ 09/03/2019

Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data

Humans are capable of learning a new behavior by observing others perfor...

Boyi Liu, et al. ∙

research

∙ 01/24/2020

Exploration Based Language Learning for Text-Based Games

This work presents an exploration and imitation-learning-based agent cap...

Andrea Madotto, et al. ∙

research

∙ 08/27/2021

MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving

Autonomous driving has attracted much attention over the years but turns...

Kai Chen, et al. ∙

research

∙ 10/11/2019

Road Damage Detection Based on Unsupervised Disparity Map Segmentation

This paper presents a novel road damage detection algorithm based on uns...

Rui Fan, et al. ∙

research

∙ 12/24/2019

A Communication Efficient Vertical Federated Learning Framework

One critical challenge for applying today's Artificial Intelligence (AI)...

Yang Liu, et al. ∙

research

∙ 02/26/2020

A Survey towards Federated Semi-supervised Learning

The success of Artificial Intelligence (AI) should be largely attributed...

Yilun Jin, et al. ∙

research

∙ 03/14/2021

Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion

We present Modular interactive VOS (MiVOS) framework which decouples int...

Ho Kei Cheng, et al. ∙

research

∙ 04/14/2022

SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study

Self-supervised pre-training methods have brought remarkable breakthroug...

Samuel Cahyawijaya, et al. ∙

research

∙ 09/06/2021

Graph Attention Layer Evolves Semantic Segmentation for Road Pothole Detection: A Benchmark and Algorithms

Existing road pothole detection approaches can be classified as computer...

Rui Fan, et al. ∙

research

∙ 11/22/2019

BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks

While deep learning has recently achieved great success on multi-view st...

Yao Yao, et al. ∙

research

∙ 03/24/2020

KFNet: Learning Temporal Camera Relocalization using Kalman Filtering

Temporal camera relocalization estimates the pose with respect to each v...

Lei Zhou, et al. ∙

research

∙ 04/16/2022

Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussion

Persuading people to change their opinions is a common practice in onlin...

Meng Xia, et al. ∙

research

∙ 06/15/2022

Prefix Language Models are Unified Modal Learners

With the success of vision-language pre-training, we have witnessed the ...

Shizhe Diao, et al. ∙

research

∙ 04/25/2019

LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeup

We propose a local adversarial disentangling network (LADN) for facial m...

Qiao Gu, et al. ∙

research

∙ 04/02/2019

Easy Transfer Learning By Exploiting Intra-domain Structures

Transfer learning aims at transferring knowledge from a well-labeled dom...

Jindong Wang, et al. ∙

research

∙ 05/17/2020

Three-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator

Over the past decade, significant efforts have been made to improve the ...

Rui Fan, et al. ∙

research

∙ 05/25/2020

Approximation in shift-invariant spaces with deep ReLU neural networks

We construct deep ReLU neural networks to approximate functions in dilat...

Yunfei Yang, et al. ∙

research

∙ 06/08/2020

Misinformation has High Perplexity

Debunking misinformation is an important and time-critical task as there...

Nayeon Lee, et al. ∙

research

∙ 01/03/2022

Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space

This paper explores the feasibility of finding an optimal sub-model from...

Arnav Chavan, et al. ∙

research

∙ 05/07/2022

Calibrating Label Distribution for Class-Imbalanced Barely-Supervised Knee Segmentation

Segmentation of 3D knee MR images is important for the assessment of ost...

Yiqun Lin, et al. ∙

research

∙ 05/01/2020

TransOMCS: From Linguistic Graphs to Commonsense Knowledge

Commonsense knowledge acquisition is a key problem for artificial intell...

Hongming Zhang, et al. ∙

research

∙ 12/03/2020

A Study on the Autoregressive and non-Autoregressive Multi-label Learning

Extreme classification tasks are multi-label tasks with an extremely lar...

Elham J. Barezi, et al. ∙

research

∙ 12/07/2018

Building Ethics into Artificial Intelligence

As artificial intelligence (AI) systems become increasingly ubiquitous, ...

Han Yu, et al. ∙

research

∙ 01/23/2020

RPN: A Residual Pooling Network for Efficient Federated Learning

Federated learning is a new machine learning framework which enables dif...

Anbu Huang, et al. ∙

research

∙ 07/15/2020

How to trust unlabeled data? Instance Credibility Inference for Few-Shot Learning

Deep learning based models have excelled in many computer vision task an...

Yikai Wang, et al. ∙

research

∙ 02/01/2021

Ground-aware Monocular 3D Object Detection for Autonomous Driving

Estimating the 3D position and orientation of objects in the environment...

YuXuan Liu, et al. ∙

research

∙ 08/19/2021

Learning to Match Features with Seeded Graph Matching Network

Matching local features across images is a fundamental problem in comput...

Hongkai Chen, et al. ∙

research

∙ 07/01/2022

A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos

Breast lesion detection in ultrasound is critical for breast cancer diag...

Zhi Lin, et al. ∙

research

∙ 12/04/2019

Plug and Play Language Models: a Simple Approach to Controlled Text Generation

Large transformer-based language models (LMs) trained on huge text corpo...

Sumanth Dathathri, et al. ∙

research

∙ 05/25/2022

Towards Diverse and Natural Scene-aware 3D Human Motion Synthesis

The ability to synthesize long-term human motion sequences in real-world...

Jingbo Wang, et al. ∙

research

∙ 06/11/2022

Federated Learning with GAN-based Data Synthesis for Non-IID Clients

Federated learning (FL) has recently emerged as a popular privacy-preser...

Zijian Li, et al. ∙

research

∙ 05/27/2019

STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems

We propose a new STAcked and Reconstructed Graph Convolutional Networks ...

Jiani Zhang, et al. ∙

research

∙ 09/10/2019

Real-time Scalable Dense Surfel Mapping

In this paper, we propose a novel dense surfel mapping system that scale...

Kaixuan Wang, et al. ∙

research

∙ 04/22/2020

Universal Masking is Urgent in the COVID-19 Pandemic: SEIR and Agent Based Models, Empirical Validation, Policy Recommendations

We present two models for the COVID-19 pandemic predicting the impact of...

De Kai, et al. ∙

research

∙ 07/23/2020

WeightNet: Revisiting the Design Space of Weight Networks

We present a conceptually simple, flexible and effective framework for w...

Ningning Ma, et al. ∙

research

∙ 12/23/2021

Learning to Walk with Dual Agents for Knowledge Graph Reasoning

Graph walking based on reinforcement learning (RL) has shown great succe...

Denghui Zhang, et al. ∙

research

∙ 03/28/2022

DNN-Driven Compressive Offloading for Edge-Assisted Semantic Video Segmentation

Deep learning has shown impressive performance in semantic segmentation,...

Xuedou Xiao, et al. ∙

research

∙ 05/12/2022

AiSocrates: Towards Answering Ethical Quandary Questions

Considerable advancements have been made in various NLP tasks based on t...

Yejin Bang, et al. ∙

research

∙ 06/14/2022

Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images

Developing an AI-assisted gland segmentation method from histology image...

Yi Li, et al. ∙

research

∙ 07/06/2022

Network Binarization via Contrastive Learning

Neural network binarization accelerates deep models by quantizing their ...

Yuzhang Shang, et al. ∙

research

∙ 07/26/2022

XInsight: eXplainable Data Analysis Through The Lens of Causality

In light of the growing popularity of Exploratory Data Analysis (EDA), u...

Pingchuan Ma, et al. ∙

research

∙ 03/03/2020

Marketplace for AI Models

Artificial intelligence shows promise for solving many practical societa...

Abhishek Kumar, et al. ∙

research

∙ 05/05/2021

Moving SLAM: Fully Unsupervised Deep Learning in Non-Rigid Scenes

We propose a method to train deep networks to decompose videos into 3D g...

Dan Xu, et al. ∙

The Hong Kong University of Science and Technology

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