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08/29/2023
A Multimodal Visual Encoding Model Aided by Introducing Verbal Semantic Information
Biological research has revealed that the verbal semantic information in...
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08/08/2023
Exploring Transformers for Open-world Instance Segmentation
Open-world instance segmentation is a rising task, which aims to segment...
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08/01/2023
Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking
Multi-Object Tracking (MOT) aims to detect and associate all desired obj...
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08/01/2023
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness
The deep neural network has attained significant efficiency in image rec...
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03/12/2023
Universal Instance Perception as Object Discovery and Retrieval
All instance perception tasks aim at finding certain objects specified b...
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10/06/2022
Dynamic Stochastic Ensemble with Adversarial Robust Lottery Ticket Subnetworks
Adversarial attacks are considered the intrinsic vulnerability of CNNs. ...
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07/14/2022
Towards Grand Unification of Object Tracking
We present a unified method, termed Unicorn, that can simultaneously sol...
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05/08/2022
Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks
The Graph Convolutional Networks (GCNs) have achieved excellent results ...
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03/25/2022
High-Performance Transformer Tracking
Correlation has a critical role in the tracking field, especially in rec...
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09/29/2021
Adaptive Multi-layer Contrastive Graph Neural Networks
We present Adaptive Multi-layer Contrastive Graph Neural Networks (AMC-G...
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06/03/2021
Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout
Deep neural networks(DNNs) is vulnerable to be attacked by adversarial e...
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05/25/2021
AdaGCN:Adaptive Boosting Algorithm for Graph Convolutional Networks on Imbalanced Node Classification
The Graph Neural Network (GNN) has achieved remarkable success in graph ...
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05/06/2021
Dynamic Defense Approach for Adversarial Robustness in Deep Neural Networks via Stochastic Ensemble Smoothed Model
Deep neural networks have been shown to suffer from critical vulnerabili...
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04/29/2021
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Object tracking has achieved significant progress over the past few year...
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03/31/2021
Learning Spatio-Temporal Transformer for Visual Tracking
In this paper, we present a new tracking architecture with an encoder-de...
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03/29/2021
Transformer Tracking
Correlation acts as a critical role in the tracking field, especially in...
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07/04/2020
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
In recent years, the multiple-stage strategy has become a popular trend ...
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03/26/2020
Neural encoding and interpretation for high-level visual cortices based on fMRI using image caption features
On basis of functional magnetic resonance imaging (fMRI), researchers ar...
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03/21/2020
Cooling-Shrinking Attack: Blinding the Tracker with Imperceptible Noises
Adversarial attack of CNN aims at deceiving models to misbehave by addin...
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03/13/2020
BigGAN-based Bayesian reconstruction of natural images from human brain activity
In the visual decoding domain, visually reconstructing presented images ...
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02/01/2020
AdvJND: Generating Adversarial Examples with Just Noticeable Difference
Compared with traditional machine learning models, deep neural networks ...
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09/17/2019
HAD-GAN: A Human-perception Auxiliary Defense GAN model to Defend Adversarial Examples
Adversarial examples reveal the vulnerability and unexplained nature of ...
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09/04/2019
'Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-term Tracking
Compared with traditional short-term tracking, long-term tracking poses ...
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07/27/2019
Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization
Recently, visual encoding based on functional magnetic resonance imaging...
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04/12/2019
Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense
In image classification of deep learning, adversarial examples where inp...
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02/23/2019
A visual encoding model based on deep neural networks and transfer learning
Background: Building visual encoding models to accurately predict visual...
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12/22/2018
Dissociable neural representations of adversarially perturbed images in deep neural networks and the human brain
Despite the remarkable similarities between deep neural networks (DNN) a...
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01/16/2018
Constraint-free Natural Image Reconstruction from fMRI Signals Based on Convolutional Neural Network
In recent years, research on decoding brain activity based on functional...
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01/02/2018
Accurate reconstruction of image stimuli from human fMRI based on the decoding model with capsule network architecture
In neuroscience, all kinds of computation models were designed to answer...
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07/29/2016
