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Nov 25, 2020
Computer Vision

Humble Teacher and Eager Student: Dual Network Learning for Semi-su…

Semi-supervised learning aims to boost the accuracy of a model by exploring unlabeled images. The state-of-the-art methods are consistency-based whic…
Nov 25, 2020
Computer Vision

We present Sparse R-CNN, a purely sparse method for object detection in images. A fixed sparse set of learned object proposals are provided to perform classification and location by dynamic heads. Final predictions are directly output without non-ma…

Sparse R-CNN: End-to-End Object Detection with Learnable Proposals

We present Sparse R-CNN, a purely sparse method for object detection in images. Existing works on object detection heavily rely on dense object candi…
Nov 17, 2020
Computer Vision
Artificial Intelligence

EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using …

Neural architecture search has proven to be highly effective in the design of computationally efficient, task-specific convolutional neural networks …
Nov 17, 2020
Computer Vision
Artificial Intelligence

EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using …

Neural architecture search has proven to be highly effective in the design of computationally efficient, task-specific convolutional neural networks …
Nov 12, 2020
Machine Learning
Artificial Intelligence
Computer Vision

A Review of Uncertainty Quantification in Deep Learning: Techniques, …

Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes. It can be …
Nov 02, 2020
Computer Vision
Robotics

Our work successfully presented a monocular vision-based architecture for mapping and localization explored under challenging agricultural environment, with new baselines provided for the relevant research community. Future works can explore other t…

SLAM in the Field: An Evaluation of Monocular Mapping and Localizatio…

This paper demonstrates a system capable of combining a sparse, indirect, monocular visual SLAM, with both offline and real-time Multi-View Stereo (M…
Nov 02, 2020
Computer Vision
Robotics

Our work successfully presented a monocular vision-based architecture for mapping and localization explored under challenging agricultural environment, with new baselines provided for the relevant research community. Future works can explore other t…

SLAM in the Field: An Evaluation of Monocular Mapping and Localizatio…

This paper demonstrates a system capable of combining a sparse, indirect, monocular visual SLAM, with both offline and real-time Multi-View Stereo (M…
Nov 02, 2020
Computer Vision
Robotics

Our work successfully presented a monocular vision-based architecture for mapping and localization explored under challenging agricultural environment, with new baselines provided for the relevant research community. Future works can explore other t…

SLAM in the Field: An Evaluation of Monocular Mapping and Localizatio…

This paper demonstrates a system capable of combining a sparse, indirect, monocular visual SLAM, with both offline and real-time Multi-View Stereo (M…
Oct 29, 2020
Computer Vision

RelationNet++: Bridging Visual Representations for Object Detection v…

Existing object detection frameworks are usually built on a single format of object/part representation, i.e., anchor/proposal rectangle boxes in Ret…
Oct 29, 2020
Computer Vision

Passport-aware Normalization for Deep Model Protection

Despite tremendous success in many application scenarios, deep learning faces serious intellectual property (IP) infringement threats. Considering th…
Oct 29, 2020
Computer Vision
Machine Learning

Black-Box Optimization of Object Detector Scales

Object detectors have improved considerably in the last years by using advanced CNN architectures. However, many detector hyper-parameters are genera…
Oct 29, 2020
Computer Vision
Machine Learning

Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural …

One-shot weight sharing methods have recently drawn great attention in neural architecture search due to high efficiency and competitive performance.…
Oct 29, 2020
Machine Learning

Tensor Completion via Tensor Networks with a Tucker Wrapper

In recent years, low-rank tensor completion (LRTC) has received considerable attention due to its applications in image/video inpainting, hyperspectr…
Oct 29, 2020
Robotics
Artificial Intelligence

A Framework for Learning Predator-prey Agents from Simulation to Real…

In this paper, we propose an evolutionary predatorprey robot system which can be generally implemented from simulation to the real world. We design t…
Oct 29, 2020
Computation and Language

Contextual BERT: Conditioning the Language Model Using a Global State

BERT is a popular language model whose main pre-training task is to fill in the blank, i.e., predicting a word that was masked out of a sentence, bas…
Oct 29, 2020
Computer Vision
Artificial Intelligence
Cryptography and Security

WaveTransform: Crafting Adversarial Examples via Input Decomposition

Frequency spectrum has played a significant role in learning unique and discriminating features for object recognition. Both low and high frequency i…
Oct 29, 2020
Sound
Machine Learning
Audio and Speech Processing

GANs & Reels: Creating Irish Music using a Generative Adversarial N…

In this paper we present a method for algorithmic melody generation using a generative adversarial network without recurrent components. Music genera…
Oct 29, 2020
Optimization and Control
Machine Learning

A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Noncon…

Nonconvex-concave min-max problem arises in many machine learning applications including minimizing a pointwise maximum of a set of nonconvex functio…
Oct 29, 2020
Computational Physics
Machine Learning
Image and Video Processing
Medical Physics

A Helmholtz equation solver using unsupervised learning: Application …

Transcranial ultrasound therapy is increasingly used for the non-invasive treatment of brain disorders. However, conventional numerical wave solvers …
Oct 29, 2020
Numerical Analysis
Machine Learning

Identifying Transition States of Chemical Kinetic Systems using Netwo…

Using random walk sampling methods for feature learning on networks, we develop a method for generating low-dimensional node embeddings for directed …
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