b'Feras Dayoub'

research

∙ 04/22/2022

Implicit Object Mapping With Noisy Data

Modelling individual objects as Neural Radiance Fields (NeRFs) within a ...

Jad Abou-Chakra, et al. ∙

research

∙ 12/10/2021

Hyperdimensional Feature Fusion for Out-Of-Distribution Detection

We introduce powerful ideas from Hyperdimensional Computing into the cha...

Samuel Wilson, et al. ∙

research

∙ 09/16/2021

Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM

Recent Semantic SLAM methods combine classical geometry-based estimation...

Suman Raj Bista, et al. ∙

research

∙ 08/19/2021

FSNet: A Failure Detection Framework for Semantic Segmentation

Semantic segmentation is an important task that helps autonomous vehicle...

Quazi Marufur Rahman, et al. ∙

research

∙ 07/24/2021

Going Deeper into Semi-supervised Person Re-identification

Person re-identification is the challenging task of identifying a person...

Olga Moskvyak, et al. ∙

research

∙ 04/03/2021

Uncertainty for Identifying Open-Set Errors in Visual Object Detection

Deployed into an open world, object detectors are prone to a type of fal...

Dimity Miller, et al. ∙

research

∙ 01/20/2021

Semi-supervised Keypoint Localization

Knowledge about the locations of keypoints of an object in an image can ...

Olga Moskvyak, et al. ∙

research

∙ 01/05/2021

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...

Quazi Marufur Rahman, et al. ∙

research

∙ 01/02/2021

Semantics for Robotic Mapping, Perception and Interaction: A Survey

For robots to navigate and interact more richly with the world around th...

Sourav Garg, et al. ∙

research

∙ 12/23/2020

SWA Object Detection

Do you want to improve 1.0 AP for your object detector without any infer...

Haoyang Zhang, et al. ∙

research

∙ 11/16/2020

Online Monitoring of Object Detection Performance Post-Deployment

Post-deployment, an object detector is expected to operate at a similar ...

Quazi Marufur Rahman, et al. ∙

research

∙ 09/18/2020

Performance Monitoring of Object Detection During Deployment

Performance monitoring of object detection is crucial for safety-critica...

Quazi Marufur Rahman, et al. ∙

research

∙ 09/11/2020

The Robotic Vision Scene Understanding Challenge

Being able to explore an environment and understand the location and typ...

David Hall, et al. ∙

research

∙ 08/31/2020

VarifocalNet: An IoU-aware Dense Object Detector

Accurately ranking a huge number of candidate detections is a key to the...

Haoyang Zhang, et al. ∙

research

∙ 08/26/2020

Keypoint-Aligned Embeddings for Image Retrieval and Re-identification

Learning embeddings that are invariant to the pose of the object is cruc...

Olga Moskvyak, et al. ∙

research

∙ 08/03/2020

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

We introduce BenchBot, a novel software suite for benchmarking the perfo...

Ben Talbot, et al. ∙

research

∙ 04/06/2020

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

Existing open set classifiers distinguish between known and unknown inpu...

Dimity Miller, et al. ∙

research

∙ 01/31/2020

Robot Navigation in Unseen Spaces using an Abstract Map

Human navigation in built environments depends on symbolic spatial infor...

Ben Talbot, et al. ∙

research

∙ 01/16/2020

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...

Jesse Haviland, et al. ∙

research

∙ 01/09/2020

Learning landmark guided embeddings for animal re-identification

Re-identification of individual animals in images can be ambiguous due t...

Olga Moskvyak, et al. ∙

research

∙ 01/08/2020

What can robotics research learn from computer vision research?

The computer vision and robotics research communities are each strong. H...

Peter Corke, et al. ∙

research

∙ 01/02/2020

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

This paper presents a novel approach to underwater terrain mapping for A...

Bilal Arain, et al. ∙

research

∙ 03/19/2019

The Probabilistic Object Detection Challenge

We introduce a new challenge for computer and robotic vision, the first ...

John Skinner, et al. ∙

research

∙ 03/15/2019

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...

Quazi Marufur Rahman, et al. ∙

research

∙ 02/28/2019

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

Visual identification of individual animals that bear unique natural bod...

Olga Moskvyak, et al. ∙

research

∙ 11/27/2018

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

We propose a new visual object detector evaluation measure which not onl...

David Hall, et al. ∙

research

∙ 09/17/2018

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

There has been a recent emergence of sampling-based techniques for estim...

Dimity Miller, et al. ∙

research

∙ 06/26/2018

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

Horticultural enterprises are becoming more sophisticated as the range o...

Ho Seok Ahn, et al. ∙

research

∙ 04/06/2018

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

This paper presents the design and implementation of an assisted control...

Aaron McFadyen, et al. ∙

research

∙ 01/25/2018

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...

David Hall, et al. ∙

research

∙ 10/18/2017

Dropout Sampling for Robust Object Detection in Open-Set Conditions

Dropout Variational Inference, or Dropout Sampling, has been recently pr...

Dimity Miller, et al. ∙

research

∙ 03/21/2017

Episode-Based Active Learning with Bayesian Neural Networks

We investigate different strategies for active learning with Bayesian de...

Feras Dayoub, et al. ∙

research

∙ 02/04/2017

Towards Unsupervised Weed Scouting for Agricultural Robotics

Weed scouting is an important part of modern integrated weed management ...

David Hall, et al. ∙

research

∙ 01/30/2017

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...

Inkyu Sa, et al. ∙

research

∙ 01/17/2015

On the Performance of ConvNet Features for Place Recognition

After the incredible success of deep learning in the computer vision dom...

Niko Sünderhauf, et al. ∙

Feras Dayoub

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