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03/21/2023
PRISE: Demystifying Deep Lucas-Kanade with Strongly Star-Convex Constraints for Multimodel Image Alignment
The Lucas-Kanade (LK) method is a classic iterative homography estimatio...
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02/02/2023
Hyperbolic Contrastive Learning
Learning good image representations that are beneficial to downstream ta...
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11/29/2022
Simultaneous Estimation of Hand Configurations and Finger Joint Angles using Forearm Ultrasound
With the advancement in computing and robotics, it is necessary to devel...
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09/27/2022
EgoSpeed-Net: Forecasting Speed-Control in Driver Behavior from Egocentric Video Data
Speed-control forecasting, a challenging problem in driver behavior anal...
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07/20/2022
Robust Object Detection With Inaccurate Bounding Boxes
Learning accurate object detectors often requires large-scale training d...
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03/29/2022
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit Gradients
Deep neural networks for 3D point cloud classification, such as PointNet...
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10/19/2021
CoFi: Coarse-to-Fine ICP for LiDAR Localization in an Efficient Long-lasting Point Cloud Map
LiDAR odometry and localization has attracted increasing research intere...
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10/14/2021
An Optimization Perspective on Realizing Backdoor Injection Attacks on Deep Neural Networks in Hardware
State-of-the-art deep neural networks (DNNs) have been proven to be vuln...
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09/23/2021
Prediction of Metacarpophalangeal joint angles and Classification of Hand configurations based on Ultrasound Imaging of the Forearm
With the advancement in computing and robotics, it is necessary to devel...
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09/13/2021
LiDAR Odometry Methodologies for Autonomous Driving: A Survey
Vehicle odometry is an essential component of an automated driving syste...
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05/23/2021
Revisiting 2D Convolutional Neural Networks for Graph-based Applications
Graph convolutional networks (GCNs) are widely used in graph-based appli...
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04/22/2021
Deep Lucas-Kanade Homography for Multimodal Image Alignment
Estimating homography to align image pairs captured by different sensors...
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04/17/2021
A Surface Geometry Model for LiDAR Depth Completion
LiDAR depth completion is a task that predicts depth values for every pi...
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04/05/2021
Branch-and-Pruning Optimization Towards Global Optimality in Deep Learning
It has been attracting more and more attention to understand the global ...
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03/03/2021
EllipsoidNet: Ellipsoid Representation for Point Cloud Classification and Segmentation
Point cloud patterns are hard to learn because of the implicit local geo...
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10/19/2020
Self-Supervised Visual Attention Learning for Vehicle Re-Identification
Visual attention learning (VAL) aims to produce a confidence map as weig...
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10/12/2020
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm
We propose a novel and efficient training method for RNNs by iteratively...
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10/02/2020
f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning
Imitation learning (IL) aims to learn a policy from expert demonstration...
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09/01/2020
LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation
Deep learning based LiDAR odometry (LO) estimation attracts increasing r...
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06/21/2020
TreeRNN: Topology-Preserving Deep GraphEmbedding and Learning
In contrast to the literature where the graph local patterns are capture...
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06/01/2020
Automatic Building and Labeling of HD Maps with Deep Learning
In a world where autonomous driving cars are becoming increasingly more ...
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03/12/2020
Learning to Segment 3D Point Clouds in 2D Image Space
In contrast to the literature where local patterns in 3D point clouds ar...
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01/05/2020
Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters
In this paper, we investigate the empirical impact of orthogonality regu...
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09/26/2019
Graph-Preserving Grid Layout: A Simple Graph Drawing Method for Graph Classification using CNNs
Graph convolutional networks (GCNs) suffer from the irregularity of grap...
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09/13/2019
White-Box Adversarial Defense via Self-Supervised Data Estimation
In this paper, we study the problem of how to defend classifiers against...
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08/31/2019
Towards Learning Affine-Invariant Representations via Data-Efficient CNNs
In this paper we propose integrating a priori knowledge into both design...
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08/27/2019
Unsupervised Deep Feature Transfer for Low Resolution Image Classification
In this paper, we propose a simple while effective unsupervised deep fea...
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08/22/2019
RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?
Recurrent neural networks (RNNs) are particularly well-suited for modeli...
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08/22/2019
RNNs Evolving in Equilibrium: A Solution to the Vanishing and Exploding Gradients
Recurrent neural networks (RNNs) are particularly well-suited for modeli...
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08/03/2019
Random Tensors and their Normal Distributions
The main purpose of this paper is to introduce the random tensor with no...
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03/26/2019
Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-Resolution Network
Face super-resolution methods usually aim at producing visually appealin...
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03/02/2019
Time-Delay Momentum: A Regularization Perspective on the Convergence and Generalization of Stochastic Momentum for Deep Learning
In this paper we study the problem of convergence and generalization err...
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03/02/2019
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability
We propose a novel Equilibrated Recurrent Neural Network (ERNN) to comb...
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05/22/2018
Deformable Part Networks
In this paper we propose novel Deformable Part Networks (DPNs) to learn ...
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05/22/2018
LMKL-Net: A Fast Localized Multiple Kernel Learning Solver via Deep Neural Networks
In this paper we propose solving localized multiple kernel learning (LMK...
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11/20/2017
Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks
By lifting the ReLU function into a higher dimensional space, we develop...
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11/19/2017
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning
Understanding the global optimality in deep learning (DL) has been attra...
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11/23/2016
Learning Joint Feature Adaptation for Zero-Shot Recognition
Zero-shot recognition (ZSR) aims to recognize target-domain data instanc...
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08/29/2016
Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning
Correlation filtering based tracking model has received lots of attentio...
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11/14/2015
Efficient Training of Very Deep Neural Networks for Supervised Hashing
In this paper, we propose training very deep neural networks (DNNs) for ...
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11/14/2015
Zero-Shot Learning via Joint Latent Similarity Embedding
Zero-shot recognition (ZSR) deals with the problem of predicting class l...
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11/14/2015
Sequential Optimization for Efficient High-Quality Object Proposal Generation
We are motivated by the need for a generic object proposal generation al...
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09/16/2015
Group Membership Prediction
The group membership prediction (GMP) problem involves predicting whethe...
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09/15/2015
Zero-Shot Learning via Semantic Similarity Embedding
In this paper we consider a version of the zero-shot learning problem wh...
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10/24/2014
A Novel Visual Word Co-occurrence Model for Person Re-identification
Person re-identification aims to maintain the identity of an individual ...
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07/20/2014
Object Proposal Generation using Two-Stage Cascade SVMs
Object proposal algorithms have shown great promise as a first step for ...
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06/13/2014
PRISM: Person Re-Identification via Structured Matching
Person re-identification (re-id), an emerging problem in visual surveill...
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02/13/2014