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MRI-based Alzheimer's disease prediction via distilling the knowledge in multi-modal data
Mild cognitive impairment (MCI) conversion prediction, i.e., identifying...
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Affordance Transfer Learning for Human-Object Interaction Detection
Reasoning the human-object interactions (HOI) is essential for deeper sc...
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Online Multiple Object Tracking with Cross-Task Synergy
Modern online multiple object tracking (MOT) methods usually focus on tw...
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Towards understanding the power of quantum kernels in the NISQ era
A key problem in the field of quantum computing is understanding whether...
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Detecting Human-Object Interaction via Fabricated Compositional Learning
Human-Object Interaction (HOI) detection, inferring the relationships be...
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Manifold Regularized Dynamic Network Pruning
Neural network pruning is an essential approach for reducing the computa...
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Learning Compositional Representation for Few-shot Visual Question Answering
Current methods of Visual Question Answering perform well on the answers...
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CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentation
Nucleus segmentation is a challenging task due to the crowded distributi...
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SLUA: A Super Lightweight Unsupervised Word Alignment Model via Cross-Lingual Contrastive Learning
Word alignment is essential for the down-streaming cross-lingual languag...
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AdderNet and its Minimalist Hardware Design for Energy-Efficient Artificial Intelligence
Convolutional neural networks (CNN) have been widely used for boosting t...
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Collaborative Teacher-Student Learning via Multiple Knowledge Transfer
Knowledge distillation (KD), as an efficient and effective model compres...
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CAA : Channelized Axial Attention for Semantic Segmentation
Self-attention and channel attention, modelling the semantic interdepend...
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Bayesian Inference Forgetting
The right to be forgotten has been legislated in many countries but the ...
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Neural networks behave as hash encoders: An empirical study
The input space of a neural network with ReLU-like activations is partit...
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SPAGAN: Shortest Path Graph Attention Network
Graph convolutional networks (GCN) have recently demonstrated their pote...
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Understanding and Improving Lexical Choice in Non-Autoregressive Translation
Knowledge distillation (KD) is essential for training non-autoregressive...
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Robustness, Privacy, and Generalization of Adversarial Training
Adversarial training can considerably robustify deep neural networks to ...
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Comprehensive Graph-conditional Similarity Preserving Network for Unsupervised Cross-modal Hashing
Unsupervised cross-modal hashing (UCMH) has become a hot topic recently....
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A Survey on Visual Transformer
Transformer is a type of deep neural network mainly based on self-attent...
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Progressive One-shot Human Parsing
Prior human parsing models are limited to parsing humans into classes pr...
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Recent advances in deep learning theory
Deep learning is usually described as an experiment-driven field under c...
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SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data
Data mixing augmentation has proved effective in training deep models. R...
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Towards Defending Multiple Adversarial Perturbations via Gated Batch Normalization
There is now extensive evidence demonstrating that deep neural networks ...
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Fast Class-wise Updating for Online Hashing
Online image hashing has received increasing research attention recently...
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SIR: Self-supervised Image Rectification via Seeing the Same Scene from Multiple Different Lenses
Deep learning has demonstrated its power in image rectification by lever...
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DUT: Learning Video Stabilization by Simply Watching Unstable Videos
We propose a Deep Unsupervised Trajectory-based stabilization framework ...
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Inter-layer Transition in Neural Architecture Search
Differential Neural Architecture Search (NAS) methods represent the netw...
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Recent Progress in Appearance-based Action Recognition
Action recognition, which is formulated as a task to identify various hu...
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Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
In the Internet of Things (IoT) era, billions of sensors and devices col...
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Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting
Deep learning is often criticized by two serious issues which rarely exi...
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Muti-view Mouse Social Behaviour Recognition with Deep Graphical Model
Home-cage social behaviour analysis of mice is an invaluable tool to ass...
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Context-Aware Cross-Attention for Non-Autoregressive Translation
Non-autoregressive translation (NAT) significantly accelerates the infer...
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End-to-end Animal Image Matting
Extracting accurate foreground animals from natural animal images benefi...
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Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning
Image-based 3D shape retrieval (IBSR) aims to find the corresponding 3D ...
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SCOP: Scientific Control for Reliable Neural Network Pruning
This paper proposes a reliable neural network pruning algorithm by setti...
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Quantum circuit architecture search: error mitigation and trainability enhancement for variational quantum solvers
Quantum error mitigation techniques are at the heart of quantum computat...
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On the Guaranteed Almost Equivalence between Imitation Learning from Observation and Demonstration
Imitation learning from observation (LfO) is more preferable than imitat...
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Pretrained Language Models for Dialogue Generation with Multiple Input Sources
Large-scale pretrained language models have achieved outstanding perform...
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Learning Propagation Rules for Attribution Map Generation
Prior gradient-based attribution-map methods rely on handcrafted propaga...
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Experimental Quantum Generative Adversarial Networks for Image Generation
Quantum machine learning is expected to be one of the first practical ap...
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Targeted Attention Attack on Deep Learning Models in Road Sign Recognition
Real world traffic sign recognition is an important step towards buildin...
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Self-supervised Exposure Trajectory Recovery for Dynamic Blur Estimation
Dynamic scene blurring is an important yet challenging topic. Recently, ...
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Open-Set Hypothesis Transfer with Semantic Consistency
Unsupervised open-set domain adaptation (UODA) is a realistic problem wh...
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Batch Coherence-Driven Network for Part-aware Person Re-Identification
Existing part-aware person re-identification methods typically employ tw...
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3D-FUTURE: 3D Furniture shape with TextURE
The 3D CAD shapes in current 3D benchmarks are mostly collected from onl...
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AdderSR: Towards Energy Efficient Image Super-Resolution
This paper studies the single image super-resolution problem using adder...
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Searching for Low-Bit Weights in Quantized Neural Networks
Quantized neural networks with low-bit weights and activations are attra...
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Heatmap Regression via Randomized Rounding
Heatmap regression has become the mainstream methodology for deep learni...
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Adaptive Context-Aware Multi-Modal Network for Depth Completion
Depth completion aims to recover a dense depth map from the sparse depth...
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Nighttime Dehazing with a Synthetic Benchmark
Increasing the visibility of nighttime hazy images is challenging becaus...
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