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08/07/2023
APBench: A Unified Benchmark for Availability Poisoning Attacks and Defenses
The efficacy of availability poisoning, a method of poisoning data by in...
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05/13/2023
GSB: Group Superposition Binarization for Vision Transformer with Limited Training Samples
Affected by the massive amount of parameters, ViT usually suffers from s...
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03/27/2023
Learning the Unlearnable: Adversarial Augmentations Suppress Unlearnable Example Attacks
Unlearnable example attacks are data poisoning techniques that can be us...
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03/15/2023
Weakly Supervised Monocular 3D Object Detection using Multi-View Projection and Direction Consistency
Monocular 3D object detection has become a mainstream approach in automa...
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01/29/2023
LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection
LiDAR devices are widely used in autonomous driving scenarios and resear...
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12/20/2022
Flareon: Stealthy any2any Backdoor Injection via Poisoned Augmentation
Open software supply chain attacks, once successful, can exact heavy cos...
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11/15/2022
MORA: Improving Ensemble Robustness Evaluation with Model-Reweighing Attack
Adversarial attacks can deceive neural networks by adding tiny perturbat...
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07/26/2022
Semi-supervised 3D Object Detection with Proficient Teachers
Dominated point cloud-based 3D object detectors in autonomous driving sc...
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07/26/2022
ProposalContrast: Unsupervised Pre-training for LiDAR-based 3D Object Detection
Existing approaches for unsupervised point cloud pre-training are constr...
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06/12/2022
Fine-tuning Pre-trained Language Models with Noise Stability Regularization
The advent of large-scale pre-trained language models has contributed gr...
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04/30/2022
Unsupervised Visible-light Images Guided Cross-Spectrum Depth Estimation from Dual-Modality Cameras
Cross-spectrum depth estimation aims to provide a depth map in all illum...
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03/22/2022
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction
Federated learning (FL) allows multiple clients to collectively train a ...
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03/14/2022
Grounding Commands for Autonomous Vehicles via Layer Fusion with Region-specific Dynamic Layer Attention
Grounding a command to the visual environment is an essential ingredient...
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12/10/2021
Boosting Active Learning via Improving Test Performance
Central to active learning (AL) is what data should be selected for anno...
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10/24/2021
SenseMag: Enabling Low-Cost Traffic Monitoring using Non-invasive Magnetic Sensing
The operation and management of intelligent transportation systems (ITS)...
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07/10/2021
Noise Stability Regularization for Improving BERT Fine-tuning
Fine-tuning pre-trained language models such as BERT has become a common...
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06/24/2021
Federated Noisy Client Learning
Federated learning (FL) collaboratively aggregates a shared global model...
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04/20/2021
Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning
Inefficient traffic control may cause numerous problems such as traffic ...
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04/19/2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features
Deep convolutional neural networks are susceptible to adversarial attack...
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03/03/2021
Adaptive Consistency Regularization for Semi-Supervised Transfer Learning
While recent studies on semi-supervised learning have shown remarkable p...
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10/16/2020
Peer-Assisted Robotic Learning: A Data-Driven Collaborative Learning Approach for Cloud Robotic Systems
A technological revolution is occurring in the field of robotics with th...
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09/07/2020
Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration
We propose an integrated approach to active exploration by exploiting th...
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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...
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12/02/2019
A Robust Stereo Camera Localization Method with Prior LiDAR Map Constrains
In complex environments, low-cost and robust localization is a challengi...
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10/21/2019
Automatic Generation of Multi-precision Multi-arithmetic CNN Accelerators for FPGAs
Modern deep Convolutional Neural Networks (CNNs) are computationally dem...
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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...
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03/07/2019
Efficient and Effective Quantization for Sparse DNNs
Deep convolutional neural networks (CNNs) are powerful tools for a wide ...
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01/23/2019
Sitatapatra: Blocking the Transfer of Adversarial Samples
Convolutional Neural Networks (CNNs) are widely used to solve classifica...
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10/12/2018