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07/27/2023
EqGAN: Feature Equalization Fusion for Few-shot Image Generation
Due to the absence of fine structure and texture information, existing f...
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07/25/2023
Curvature-based Transformer for Molecular Property Prediction
The prediction of molecular properties is one of the most important and ...
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06/13/2023
Hyperbolic Graph Diffusion Model for Molecule Generation
Recently, diffusion models have achieved remarkable performance in data ...
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04/26/2023
Group Equivariant BEV for 3D Object Detection
Recently, 3D object detection has attracted significant attention and ac...
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04/16/2023
Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations
Autoencoders have achieved great success in various computer vision appl...
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04/12/2023
Multi-scale Geometry-aware Transformer for 3D Point Cloud Classification
Self-attention modules have demonstrated remarkable capabilities in capt...
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02/27/2023
DuEqNet: Dual-Equivariance Network in Outdoor 3D Object Detection for Autonomous Driving
Outdoor 3D object detection has played an essential role in the environm...
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02/16/2023
A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold
Although Deep Learning (DL) has achieved success in complex Artificial I...
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01/28/2023
CyclicFL: A Cyclic Model Pre-Training Approach to Efficient Federated Learning
Since random initial models in Federated Learning (FL) can easily result...
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12/05/2022
HierarchyFL: Heterogeneous Federated Learning via Hierarchical Self-Distillation
Federated learning (FL) has been recognized as a privacy-preserving dist...
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09/17/2022
Hand and Arm Gesture-based Human-Robot Interaction: A Review
The study of Human-Robot Interaction (HRI) aims to create close and frie...
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09/11/2022
Continual Learning for Pose-Agnostic Object Recognition in 3D Point Clouds
Continual Learning aims to learn multiple incoming new tasks continually...
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08/16/2022
FedMR: Fedreated Learning via Model Recombination
As a promising privacy-preserving machine learning method, Federated Lea...
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05/09/2022
Model-Contrastive Learning for Backdoor Defense
Along with the popularity of Artificial Intelligence (AI) techniques, an...
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04/21/2022
Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation
Due to the prosperity of Artificial Intelligence (AI) techniques, more a...
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03/11/2022
Learning from Attacks: Attacking Variational Autoencoder for Improving Image Classification
Adversarial attacks are often considered as threats to the robustness of...
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02/03/2022
SparGE: Sparse Coding-based Patient Similarity Learning via Low-rank Constraints and Graph Embedding
Patient similarity assessment (PSA) is pivotal to evidence-based and per...
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01/28/2022
O-ViT: Orthogonal Vision Transformer
Inspired by the tremendous success of the self-attention mechanism in na...
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01/05/2022
Synthesizing Tensor Transformations for Visual Self-attention
Self-attention shows outstanding competence in capturing long-range rela...
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12/27/2021
Learning Robust and Lightweight Model through Separable Structured Transformations
With the proliferation of mobile devices and the Internet of Things, dee...
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12/27/2021
ViR:the Vision Reservoir
The most recent year has witnessed the success of applying the Vision Tr...
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12/10/2021
Couplformer:Rethinking Vision Transformer with Coupling Attention Map
With the development of the self-attention mechanism, the Transformer mo...
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11/29/2021
Efficient Federated Learning for AIoT Applications Using Knowledge Distillation
As a promising distributed machine learning paradigm, Federated Learning...
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10/03/2021
Boost Neural Networks by Checkpoints
Training multiple deep neural networks (DNNs) and averaging their output...
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04/01/2019
Deep Clustering With Intra-class Distance Constraint for Hyperspectral Images
The high dimensionality of hyperspectral images often results in the deg...
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03/24/2019
Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections
This work investigates the problem of efficiently learning discriminativ...
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03/23/2019
1D-Convolutional Capsule Network for Hyperspectral Image Classification
Recently, convolutional neural networks (CNNs) have achieved excellent p...
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10/08/2018
Trace Quotient with Sparsity Priors for Learning Low Dimensional Image Representations
This work studies the problem of learning appropriate low dimensional im...
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12/19/2013