Feras Dayoub

verfied profile

My research interests are focused on enabling real mobile robots to operate persistently and reliably using computer vision and machine learning in challenging environments, environments that are real, complex and continually changing.

Uncertainty for Identifying Open-Set Errors in Visual Object Detection

Deployed into an open world, object detectors are prone to a type of fal...
04/03/2021 ∙ by Dimity Miller, et al. ∙ 0 ∙ share

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Semi-supervised Keypoint Localization

Knowledge about the locations of keypoints of an object in an image can ...
01/20/2021 ∙ by Olga Moskvyak, et al. ∙ 0 ∙ share

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Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends

As deep learning continues to dominate all state-of-the-art computer vis...
01/05/2021 ∙ by Quazi Marufur Rahman, et al. ∙ 0 ∙ share

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Semantics for Robotic Mapping, Perception and Interaction: A Survey

For robots to navigate and interact more richly with the world around th...
01/02/2021 ∙ by Sourav Garg, et al. ∙ 0 ∙ share

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SWA Object Detection

Do you want to improve 1.0 AP for your object detector without any infer...
12/23/2020 ∙ by Haoyang Zhang, et al. ∙ 13 ∙ share

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Online Monitoring of Object Detection Performance Post-Deployment

Post-deployment, an object detector is expected to operate at a similar ...
11/16/2020 ∙ by Quazi Marufur Rahman, et al. ∙ 11 ∙ share

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Performance Monitoring of Object Detection During Deployment

Performance monitoring of object detection is crucial for safety-critica...
09/18/2020 ∙ by Quazi Marufur Rahman, et al. ∙ 7 ∙ share

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The Robotic Vision Scene Understanding Challenge

Being able to explore an environment and understand the location and typ...
09/11/2020 ∙ by David Hall, et al. ∙ 0 ∙ share

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VarifocalNet: An IoU-aware Dense Object Detector

Accurately ranking a huge number of candidate detections is a key to the...
08/31/2020 ∙ by Haoyang Zhang, et al. ∙ 18 ∙ share

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Keypoint-Aligned Embeddings for Image Retrieval and Re-identification

Learning embeddings that are invariant to the pose of the object is cruc...
08/26/2020 ∙ by Olga Moskvyak, et al. ∙ 17 ∙ share

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BenchBot: Evaluating Robotics Research in Photorealistic 3D Simulation and on Real Robots

We introduce BenchBot, a novel software suite for benchmarking the perfo...
08/03/2020 ∙ by Ben Talbot, et al. ∙ 0 ∙ share

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Class Anchor Clustering: a Distance-based Loss for Training Open Set Classifiers

Existing open set classifiers distinguish between known and unknown inpu...
04/06/2020 ∙ by Dimity Miller, et al. ∙ 26 ∙ share

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Robot Navigation in Unseen Spaces using an Abstract Map

Human navigation in built environments depends on symbolic spatial infor...
01/31/2020 ∙ by Ben Talbot, et al. ∙ 6 ∙ share

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Predicting Target Feature Configuration of Non-stationary Objects for Grasping with Image-Based Visual Servoing

In this paper we consider the problem of the final approach stage of clo...
01/16/2020 ∙ by Jesse Haviland, et al. ∙ 6 ∙ share

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Learning landmark guided embeddings for animal re-identification

Re-identification of individual animals in images can be ambiguous due t...
01/09/2020 ∙ by Olga Moskvyak, et al. ∙ 9 ∙ share

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What can robotics research learn from computer vision research?

The computer vision and robotics research communities are each strong. H...
01/08/2020 ∙ by Peter Corke, et al. ∙ 50 ∙ share

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Close-Proximity Underwater Terrain Mapping Using Learning-based Coarse Range Estimation

This paper presents a novel approach to underwater terrain mapping for A...
01/02/2020 ∙ by Bilal Arain, et al. ∙ 0 ∙ share

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The Probabilistic Object Detection Challenge

We introduce a new challenge for computer and robotic vision, the first ...
03/19/2019 ∙ by John Skinner, et al. ∙ 0 ∙ share

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Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors

Object detection is an integral part of an autonomous vehicle for its sa...
03/15/2019 ∙ by Quazi Marufur Rahman, et al. ∙ 0 ∙ share

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Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings

Visual identification of individual animals that bear unique natural bod...
02/28/2019 ∙ by Olga Moskvyak, et al. ∙ 18 ∙ share

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Probability-based Detection Quality (PDQ): A Probabilistic Approach to Detection Evaluation

We propose a new visual object detector evaluation measure which not onl...
11/27/2018 ∙ by David Hall, et al. ∙ 0 ∙ share

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Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection

There has been a recent emergence of sampling-based techniques for estim...
09/17/2018 ∙ by Dimity Miller, et al. ∙ 8 ∙ share

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An Overview of Perception Methods for Horticultural Robots: From Pollination to Harvest

Horticultural enterprises are becoming more sophisticated as the range o...
06/26/2018 ∙ by Ho Seok Ahn, et al. ∙ 0 ∙ share

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Assisted Control for Semi-Autonomous Power Infrastructure Inspection using Aerial Vehicles

This paper presents the design and implementation of an assisted control...
04/06/2018 ∙ by Aaron McFadyen, et al. ∙ 0 ∙ share

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A Rapidly Deployable Classification System using Visual Data for the Application of Precision Weed Management

In this work we demonstrate a rapidly deployable weed classification sys...
01/25/2018 ∙ by David Hall, et al. ∙ 0 ∙ share

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Dropout Sampling for Robust Object Detection in Open-Set Conditions

Dropout Variational Inference, or Dropout Sampling, has been recently pr...
10/18/2017 ∙ by Dimity Miller, et al. ∙ 0 ∙ share

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Episode-Based Active Learning with Bayesian Neural Networks

We investigate different strategies for active learning with Bayesian de...
03/21/2017 ∙ by Feras Dayoub, et al. ∙ 0 ∙ share

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Towards Unsupervised Weed Scouting for Agricultural Robotics

Weed scouting is an important part of modern integrated weed management ...
02/04/2017 ∙ by David Hall, et al. ∙ 0 ∙ share

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Peduncle Detection of Sweet Pepper for Autonomous Crop Harvesting - Combined Colour and 3D Information

This paper presents a 3D visual detection method for the challenging tas...
01/30/2017 ∙ by Inkyu Sa, et al. ∙ 0 ∙ share

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On the Performance of ConvNet Features for Place Recognition

After the incredible success of deep learning in the computer vision dom...
01/17/2015 ∙ by Niko Sünderhauf, et al. ∙ 0 ∙ share

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Feras Dayoub

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