b'Wenbin Li'

research

∙ 03/17/2023

Causal Discovery from Temporal Data: An Overview and New Perspectives

Temporal data, representing chronological observations of complex system...

0 Chang Gong, et al. ∙

research

∙ 03/12/2023

RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning

Gradient-based meta-learning (GBML) algorithms are able to fast adapt to...

0 Min Zhang, et al. ∙

research

∙ 03/03/2023

A Visual SLAM with Moving Object Trajectory Prediction

Visual Simultaneous Localization and Mapping (SLAM) has received signifi...

0 Qi Zhang, et al. ∙

research

∙ 03/02/2023

Resource-Constrained Station-Keeping for Helium Balloons using Reinforcement Learning

High altitude balloons have proved useful for ecological aerial surveys,...

0 Jack Saunders, et al. ∙

research

∙ 02/16/2023

A Review and a Taxonomy of Edge Machine Learning: Requirements, Paradigms, and Techniques

The union of Edge Computing (EC) and Artificial Intelligence (AI) has br...

0 Wenbin Li, et al. ∙

research

∙ 10/10/2022

Deep object detection for waterbird monitoring using aerial imagery

Monitoring of colonial waterbird nesting islands is essential to trackin...

0 Krish Kabra, et al. ∙

research

∙ 10/10/2022

Learning Credit Assignment for Cooperative Reinforcement Learning

Cooperative multi-agent policy gradient (MAPG) algorithms have recently ...

2 Wubing Chen, et al. ∙

research

∙ 10/07/2022

Uniformly convex neural networks and non-stationary iterated network Tikhonov (iNETT) method

We propose a non-stationary iterated network Tikhonov (iNETT) method for...

0 Davide Bianchi, et al. ∙

research

∙ 09/22/2022

Parallel Reinforcement Learning Simulation for Visual Quadrotor Navigation

Reinforcement learning (RL) is an agent-based approach for teaching robo...

0 Jack Saunders, et al. ∙

research

∙ 07/22/2022

Dense RGB-D-Inertial SLAM with Map Deformations

While dense visual SLAM methods are capable of estimating dense reconstr...

0 Tristan Laidlow, et al. ∙

research

∙ 07/14/2022

Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation

In this paper, we mainly focus on the problem of how to learn additional...

0 Min Zhang, et al. ∙

research

∙ 01/11/2022

A stochastic gradient descent approach with partitioned-truncated singular value decomposition for large-scale inverse problems of magnetic modulus data

We propose a stochastic gradient descent approach with partitioned-trunc...

0 Wenbin Li, et al. ∙

research

∙ 10/06/2021

Autonomous Aerial Delivery Vehicles, a Survey of Techniques on how Aerial Package Delivery is Achieved

Autonomous aerial delivery vehicles have gained significant interest in ...

0 Jack Saunders, et al. ∙

research

∙ 07/13/2020

Embedded Deep Bilinear Interactive Information and Selective Fusion for Multi-view Learning

As a concrete application of multi-view learning, multi-view classificat...

0 Jinglin Xu, et al. ∙

research

∙ 04/21/2020

Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification

Skin disease classification from images is crucial to dermatological dia...

0 Wei Zhu, et al. ∙

research

∙ 04/16/2020

RGBD-Dog: Predicting Canine Pose from RGBD Sensors

The automatic extraction of animal 3D pose from images without markers i...

18 Sinead Kearney, et al. ∙

research

∙ 12/18/2019

Class Regularization: Improve Few-shot Image Classification by Reducing Meta Shift

Few-shot image classification requires the classifier to robustly cope w...

0 Da Chen, et al. ∙

research

∙ 04/19/2019

Learning Manipulation under Physics Constraints with Visual Perception

Understanding physical phenomena is a key competence that enables humans...

0 Wenbin Li, et al. ∙

research

∙ 03/28/2019

Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning

Few-shot learning in image classification aims to learn a classifier to ...

0 Wenbin Li, et al. ∙

research

∙ 12/19/2018

MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM

We propose a new multi-instance dynamic RGB-D SLAM system using an objec...

0 Binbin Xu, et al. ∙

research

∙ 11/01/2018

CariGAN: Caricature Generation through Weakly Paired Adversarial Learning

Caricature generation is an interesting yet challenging task. The primar...

12 Wenbin Li, et al. ∙

research

∙ 09/03/2018

InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset

Datasets have gained an enormous amount of popularity in the computer vi...

1 Wenbin Li, et al. ∙

research

∙ 05/15/2018

Online Deep Metric Learning

Metric learning learns a metric function from training data to calculate...

0 Wenbin Li, et al. ∙

research

∙ 11/01/2017

Acquiring Target Stacking Skills by Goal-Parameterized Deep Reinforcement Learning

Understanding physical phenomena is a key component of human intelligenc...

0 Wenbin Li, et al. ∙

research

∙ 09/19/2017

Automatic Structural Scene Digitalization

In this paper, we present an automatic system for the analysis and label...

0 Rui Tang, et al. ∙

research

∙ 03/09/2017

WebCaricature: a benchmark for caricature face recognition

Caricatures are facial drawings by artists with exaggeration on certain ...

0 Jing Huo, et al. ∙

research

∙ 09/29/2016

OPML: A One-Pass Closed-Form Solution for Online Metric Learning

To achieve a low computational cost when performing online metric learni...

0 Wenbin Li, et al. ∙

research

∙ 09/15/2016

Visual Stability Prediction and Its Application to Manipulation

Understanding physical phenomena is a key competence that enables humans...

0 Wenbin Li, et al. ∙

research

∙ 09/07/2016

Dense Motion Estimation for Smoke

Motion estimation for highly dynamic phenomena such as smoke is an open ...

0 Da Chen, et al. ∙

research

∙ 03/31/2016

To Fall Or Not To Fall: A Visual Approach to Physical Stability Prediction

Understanding physical phenomena is a key competence that enables humans...

0 Wenbin Li, et al. ∙

research

∙ 03/26/2016

Video Interpolation using Optical Flow and Laplacian Smoothness

Non-rigid video interpolation is a common computer vision task. In this ...

0 Wenbin Li, et al. ∙

research

∙ 03/26/2016

Nonrigid Optical Flow Ground Truth for Real-World Scenes with Time-Varying Shading Effects

In this paper we present a dense ground truth dataset of nonrigidly defo...

0 Wenbin Li, et al. ∙

research

∙ 03/07/2016

Blur Robust Optical Flow using Motion Channel

It is hard to estimate optical flow given a realworld video sequence wit...

0 Wenbin Li, et al. ∙

research

∙ 03/07/2016

Drift Robust Non-rigid Optical Flow Enhancement for Long Sequences

It is hard to densely track a nonrigid object in long term, which is a f...

0 Wenbin Li, et al. ∙

research

∙ 08/13/2014

Learning Multi-Scale Representations for Material Classification

The recent progress in sparse coding and deep learning has made unsuperv...

0 Wenbin Li, et al. ∙

Wenbin Li

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