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Improved Techniques for Model Inversion Attacks
Model inversion (MI) attacks in the whitebox setting are aimed at recons...
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K-Shot Contrastive Learning of Visual Features with Multiple Instance Augmentations
In this paper, we propose the K-Shot Contrastive Learning (KSCL) of visu...
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Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events
Along with the development of the modern smart city, human-centric video...
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Spatial-Temporal Transformer Networks for Traffic Flow Forecasting
Traffic forecasting has emerged as a core component of intelligent trans...
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EnAET: Self-Trained Ensemble AutoEncoding Transformations for Semi-Supervised Learning
Deep neural networks have been successfully applied to many real-world a...
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GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations
Recent advances in Graph Convolutional Neural Networks (GCNNs) have show...
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AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups
Self-supervised learning by predicting transformations has demonstrated ...
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Progressive Unsupervised Person Re-identification by Tracklet Association with Spatio-Temporal Regularization
Existing methods for person re-identification (Re-ID) are mostly based o...
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Spatiotemporal Co-attention Recurrent Neural Networks for Human-Skeleton Motion Prediction
Human motion prediction aims to generate future motions based on the obs...
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PC-DARTS: Partial Channel Connections for Memory-Efficient Differentiable Architecture Search
Differentiable architecture search (DARTS) provided a fast solution in f...
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Learning Generalized Transformation Equivariant Representations via Autoencoding Transformations
Learning Transformation Equivariant Representations (TERs) seeks to capt...
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Differential Recurrent Neural Network and its Application for Human Activity Recognition
The Long Short-Term Memory (LSTM) recurrent neural network is capable of...
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Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods
Small data challenges have emerged in many learning problems, since the ...
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AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations
The learning of Transformation-Equivariant Representations (TERs), which...
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Learning to Adaptively Scale Recurrent Neural Networks
Recent advancements in recurrent neural network (RNN) research have demo...
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AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data
The success of deep neural networks often relies on a large amount of la...
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Deep Semantic Multimodal Hashing Network for Scalable Multimedia Retrieval
Hashing has been widely applied to multimodal retrieval on large-scale m...
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Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition
In this paper, we aim to address the problem of human interaction recogn...
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A Study of Question Effectiveness Using Reddit "Ask Me Anything" Threads
Asking effective questions is a powerful social skill. In this paper we ...
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Task-Agnostic Meta-Learning for Few-shot Learning
Meta-learning approaches have been proposed to tackle the few-shot learn...
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CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces
In this paper, we formalize the idea behind capsule nets of using a caps...
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Deep Ordinal Hashing with Spatial Attention
Hashing has attracted increasing research attentions in recent years due...
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Sharp Attention Network via Adaptive Sampling for Person Re-identification
In this paper, we present novel sharp attention networks by adaptively s...
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IGCV2: Interleaved Structured Sparse Convolutional Neural Networks
In this paper, we study the problem of designing efficient convolutional...
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Deep Differential Recurrent Neural Networks
Due to the special gating schemes of Long Short-Term Memory (LSTM), LSTM...
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Global versus Localized Generative Adversarial Nets
In this paper, we present a novel localized Generative Adversarial Net (...
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Interleaved Group Convolutions for Deep Neural Networks
In this paper, we present a simple and modularized neural network archit...
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Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition
Recently, Long Short-Term Memory (LSTM) has become a popular choice to m...
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Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes
In this paper, we present a label transfer model from texts to images fo...
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Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities
*New Theory Result* We analyze the generalizability of the LS-GAN, showi...
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First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos
With the prevalence of the commodity depth cameras, the new paradigm of ...
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Differential Recurrent Neural Networks for Action Recognition
The long short-term memory (LSTM) neural network is capable of processin...
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