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07/18/2023
Exploiting Field Dependencies for Learning on Categorical Data
Traditional approaches for learning on categorical data underexploit the...
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07/07/2023
Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification Segmentation
We address the task of weakly-supervised few-shot image classification a...
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05/09/2023
Message Passing Neural Networks for Traffic Forecasting
A road network, in the context of traffic forecasting, is typically mode...
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05/09/2023
Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training
New roads are being constructed all the time. However, the capabilities ...
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02/20/2023
Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting
Traffic forecasting is a critical task to extract values from cyber-phys...
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02/14/2023
Event-guided Multi-patch Network with Self-supervision for Non-uniform Motion Deblurring
Contemporary deep learning multi-scale deblurring models suffer from man...
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03/26/2022
Accurate 3-DoF Camera Geo-Localization via Ground-to-Satellite Image Matching
We address the problem of ground-to-satellite image geo-localization, th...
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01/15/2022
Multi-level Second-order Few-shot Learning
We propose a Multi-level Second-order (MlSo) few-shot learning network f...
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12/23/2021
Manifold Learning Benefits GANs
In this paper, we improve Generative Adversarial Networks by incorporati...
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12/12/2021
Few-shot Keypoint Detection with Uncertainty Learning for Unseen Species
Current non-rigid object keypoint detectors perform well on a chosen kin...
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10/26/2021
Meta-Learning for Multi-Label Few-Shot Classification
Even with the luxury of having abundant data, multi-label classification...
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10/23/2021
Towards a Robust Differentiable Architecture Search under Label Noise
Neural Architecture Search (NAS) is the game changer in designing robust...
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10/22/2021
Simple Dialogue System with AUDITED
We devise a multimodal conversation system for dialogue utterances compo...
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05/19/2021
Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map
To model and forecast flight delays accurately, it is crucial to harness...
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04/17/2021
On Learning the Geodesic Path for Incremental Learning
Neural networks notoriously suffer from the problem of catastrophic forg...
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12/27/2020
Power Normalizations in Fine-grained Image, Few-shot Image and Graph Classification
Power Normalizations (PN) are useful non-linear operators which tackle f...
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09/23/2020
A Token-wise CNN-based Method for Sentence Compression
Sentence compression is a Natural Language Processing (NLP) task aimed a...
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02/10/2020
6DoF Object Pose Estimation via Differentiable Proxy Voting Loss
Estimating a 6DOF object pose from a single image is very challenging du...
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01/12/2020
Rethinking Class Relations: Absolute-relative Few-shot Learning
The majority of existing few-shot learning describe image relations with...
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01/12/2020
Few-shot Action Recognition via Improved Attention with Self-supervision
Most existing few-shot learning methods in computer vision focus on clas...
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01/06/2020
Few-shot Learning with Multi-scale Self-supervision
Learning concepts from the limited number of datapoints is a challenging...
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09/24/2019
COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference
The process of automatic generation of a road map from GPS trajectories,...
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06/24/2019
A Comparative Review of Recent Kinect-based Action Recognition Algorithms
Video-based human action recognition is currently one of the most active...
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06/13/2019
Hallucinating Bag-of-Words and Fisher Vector IDT terms for CNN-based Action Recognition
In this paper, we revive the use of old-fashioned handcrafted video repr...
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04/07/2019
Recovering Faces from Portraits with Auxiliary Facial Attributes
Recovering a photorealistic face from an artistic portrait is a challeng...
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04/07/2019
Identity-preserving Face Recovery from Stylized Portraits
Given an artistic portrait, recovering the latent photorealistic face th...
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04/06/2019
Few-Shot Learning via Saliency-guided Hallucination of Samples
Learning new concepts from a few of samples is a standard challenge in c...
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04/06/2019
Deep Stacked Hierarchical Multi-patch Network for Image Deblurring
Despite deep end-to-end learning methods have shown their superiority in...
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03/11/2019
Fisher-Bures Adversary Graph Convolutional Networks
In a graph convolutional network, we assume that the graph G is generate...
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11/10/2018
Power Normalizing Second-order Similarity Network for Few-shot Learning
Second- and higher-order statistics of data points have played an import...
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11/08/2018
Model Selection for Generalized Zero-shot Learning
In the problem of generalized zero-shot learning, the datapoints from un...
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08/22/2018
Second-order Democratic Aggregation
Aggregated second-order features extracted from deep convolutional netwo...
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06/24/2018
A Deeper Look at Power Normalizations
Power Normalizations (PN) are very useful non-linear operators in the co...
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06/24/2018
Artwork Identification from Wearable Camera Images for Enhancing Experience of Museum Audiences
Recommendation systems based on image recognition could prove a vital to...
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06/24/2018
CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps
Deep learning is ubiquitous across many areas areas of computer vision. ...
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02/05/2018
Zero-Shot Kernel Learning
In this paper, we address an open problem of zero-shot learning. Its pri...
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02/05/2018
Face Destylization
Numerous style transfer methods which produce artistic styles of portrai...
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02/04/2018
Museum Exhibit Identification Challenge for Domain Adaptation and Beyond
In this paper, we approach an open problem of artwork identification and...
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01/08/2018
Identity-preserving Face Recovery from Portraits
Recovering the latent photorealistic faces from their artistic portraits...
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01/19/2017
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition
Most successful deep learning algorithms for action recognition extend m...
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11/24/2016
Domain Adaptation by Mixture of Alignments of Second- or Higher-Order Scatter Tensors
In this paper, we propose an approach to the domain adaptation, dubbed S...
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04/01/2016
Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons (Extended Version)
In this paper, we explore tensor representations that can compactly capt...
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09/09/2015
Dictionary Learning and Sparse Coding for Third-order Super-symmetric Tensors
Super-symmetric tensors - a higher-order extension of scatter matrices -...
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06/12/2014
