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09/15/2023
STDG: Semi-Teacher-Student Training Paradigram for Depth-guided One-stage Scene Graph Generation
Scene Graph Generation is a critical enabler of environmental comprehens...
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09/02/2023
Drift Analysis with Fitness Levels for Elitist Evolutionary Algorithms
The fitness level method is a popular tool for analyzing the computation...
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03/25/2023
Backdoor Attacks with Input-unique Triggers in NLP
Backdoor attack aims at inducing neural models to make incorrect predict...
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03/14/2023
Subjective and Objective Quality Assessment for in-the-Wild Computer Graphics Images
Computer graphics images (CGIs) are artificially generated by means of c...
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12/22/2022
SHLE: Devices Tracking and Depth Filtering for Stereo-based Height Limit Estimation
Recently, over-height vehicle strike frequently occurs, causing great ec...
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11/30/2022
FuRPE: Learning Full-body Reconstruction from Part Experts
Full-body reconstruction is a fundamental but challenging task. Owing to...
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09/23/2022
GIDP: Learning a Good Initialization and Inducing Descriptor Post-enhancing for Large-scale Place Recognition
Large-scale place recognition is a fundamental but challenging task, whi...
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09/17/2022
Human Pose Driven Object Effects Recommendation
In this paper, we research the new topic of object effects recommendatio...
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09/01/2022
MM-PCQA: Multi-Modal Learning for No-reference Point Cloud Quality Assessment
The visual quality of point clouds has been greatly emphasized since the...
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07/12/2022
Domain Gap Estimation for Source Free Unsupervised Domain Adaptation with Many Classifiers
In theory, the success of unsupervised domain adaptation (UDA) largely r...
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06/09/2022
Deep Neural Network for Blind Visual Quality Assessment of 4K Content
The 4K content can deliver a more immersive visual experience to consume...
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04/20/2022
Reconstruction-Aware Prior Distillation for Semi-supervised Point Cloud Completion
Point clouds scanned by real-world sensors are always incomplete, irregu...
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04/04/2022
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image
Recently, RGBD-based category-level 6D object pose estimation has achiev...
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12/16/2021
BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing
Graph neural networks (GNNs) have extended the success of deep neural ne...
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11/20/2021
ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation
Recently, category-level 6D object pose estimation has achieved signific...
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09/29/2021
Influence of the Binomial Crossover on Performance of Evolutionary Algorithms
In differential Evolution (DE) algorithms, a crossover operation filteri...
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09/14/2021
An MRC Framework for Semantic Role Labeling
Semantic Role Labeling (SRL) aims at recognizing the predicate-argument ...
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08/29/2021
Attentive Rotation Invariant Convolution for Point Cloud-based Large Scale Place Recognition
Autonomous Driving and Simultaneous Localization and Mapping(SLAM) are b...
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06/16/2021
Improving Entity Linking through Semantic Reinforced Entity Embeddings
Entity embeddings, which represent different aspects of each entity with...
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05/29/2021
Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview
Object pose detection and tracking has recently attracted increasing att...
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05/01/2021
SVT-Net: A Super Light-Weight Network for Large Scale Place Recognition using Sparse Voxel Transformers
Point cloud-based large scale place recognition is fundamental for many ...
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03/30/2021
Revisiting Deep Local Descriptor for Improved Few-Shot Classification
Few-shot classification studies the problem of quickly adapting a deep l...
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10/17/2020
LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
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06/25/2020
DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors
Human activity recognition (HAR) in ubiquitous computing has been beginn...
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06/05/2020
Real-time Human Activity Recognition Using Conditionally Parametrized Convolutions on Mobile and Wearable Devices
Recently, deep learning has represented an important research trend in h...
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05/09/2020
Memory-Augmented Relation Network for Few-Shot Learning
Metric-based few-shot learning methods concentrate on learning transfera...
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05/08/2020
Efficient convolutional neural networks with smaller filters for human activity recognition using wearable sensors
Recently, human activity recognition (HAR) has been beginning to adopt d...
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04/17/2020
Incorporating Multiple Cluster Centers for Multi-Label Learning
Multi-label learning deals with the problem that each instance is associ...
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04/13/2020
Sequential Weakly Labeled Multi-Activity Recognition and Location on Wearable Sensors using Recurrent Attention Network
With the popularity and development of the wearable devices such as smar...
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01/29/2020
Exploitation and Exploration Analysis of Elitist Evolutionary Algorithms: A Case Study
Known as two cornerstones of problem solving by search, exploitation and...
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11/11/2019
Conditionally Learn to Pay Attention for Sequential Visual Task
Sequential visual task usually requires to pay attention to its current ...
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09/07/2019
Unlimited Budget Analysis of Randomised Search Heuristics
Performance analysis of all kinds of randomised search heuristics is a r...
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09/03/2019
Estimating Approximation Errors of Elitist Evolutionary Algorithms
When EAs are unlikely to locate precise global optimal solutions with sa...
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03/24/2019
Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors
Unlike images or videos data which can be easily labeled by human being,...
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10/27/2018
Average Convergence Rate of Evolutionary Algorithms II: Continuous Optimization
A good convergence metric must satisfy two requirements: feasible in cal...
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10/26/2018
A Theoretical Framework of Approximation Error Analysis of Evolutionary Algorithms
In the empirical study of evolutionary algorithms, the solution quality ...
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10/11/2018
A Blended Deep Learning Approach for Predicting User Intended Actions
User intended actions are widely seen in many areas. Forecasting these a...
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05/01/2018
Multiobjective Optimization Differential Evolution Enhanced with Principle Component Analysis for Constrained Optimization
Multiobjective optimization evolutionary algorithms have been successful...
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04/30/2018
New Methods of Studying Valley Fitness Landscapes
The word "valley" is a popular term used in intuitively describing fitne...
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11/11/2015
An Analytic Expression of Relative Approximation Error for a Class of Evolutionary Algorithms
An important question in evolutionary computation is how good solutions ...
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09/30/2015
Multi-objective Differential Evolution with Helper Functions for Constrained Optimization
Solving constrained optimization problems by multi-objective evolutionar...
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04/30/2015
Average Convergence Rate of Evolutionary Algorithms
In evolutionary optimization, it is important to understand how fast evo...
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02/12/2015
Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem
Multi-objective optimisation is regarded as one of the most promising wa...
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12/12/2014
Adaptive Stochastic Gradient Descent on the Grassmannian for Robust Low-Rank Subspace Recovery and Clustering
In this paper, we present GASG21 (Grassmannian Adaptive Stochastic Gradi...
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09/03/2014
Performance Analysis on Evolutionary Algorithms for the Minimum Label Spanning Tree Problem
Some experimental investigations have shown that evolutionary algorithms...
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04/14/2014
A Theoretical Assessment of Solution Quality in Evolutionary Algorithms for the Knapsack Problem
Evolutionary algorithms are well suited for solving the knapsack problem...
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04/03/2014
A Novel Genetic Algorithm using Helper Objectives for the 0-1 Knapsack Problem
The 0-1 knapsack problem is a well-known combinatorial optimisation prob...
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12/09/2013
A Unified Markov Chain Approach to Analysing Randomised Search Heuristics
The convergence, convergence rate and expected hitting time play fundame...
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08/14/2013
Average Drift Analysis and Population Scalability
This paper aims to study how the population size affects the computation...
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06/03/2013
