b'Ian Reid'

research

∙ 07/12/2023

SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Task Planning

Large language models (LLMs) have demonstrated impressive results in dev...

0 Krishan Rana, et al. ∙

research

∙ 07/04/2023

Semantic Segmentation on 3D Point Clouds with High Density Variations

LiDAR scanning for surveying applications acquire measurements over wide...

0 Ryan Faulkner, et al. ∙

research

∙ 11/23/2022

ActiveRMAP: Radiance Field for Active Mapping And Planning

A high-quality 3D reconstruction of a scene from a collection of 2D imag...

0 Huangying Zhan, et al. ∙

research

∙ 11/23/2022

Predicting Topological Maps for Visual Navigation in Unexplored Environments

We propose a robotic learning system for autonomous exploration and navi...

0 Huangying Zhan, et al. ∙

research

∙ 11/14/2022

What Images are More Memorable to Machines?

This paper studies the problem of measuring and predicting how memorable...

0 Junlin Han, et al. ∙

research

∙ 11/07/2022

SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes

Self-supervised monocular depth estimation has shown impressive results ...

0 Libo Sun, et al. ∙

research

∙ 09/27/2022

Globally Optimal Event-Based Divergence Estimation for Ventral Landing

Event sensing is a major component in bio-inspired flight guidance and c...

5 Sofia McLeod, et al. ∙

research

∙ 05/31/2022

CropMix: Sampling a Rich Input Distribution via Multi-Scale Cropping

We present a simple method, CropMix, for the purpose of producing a rich...

2 Junlin Han, et al. ∙

research

∙ 03/02/2022

Asynchronous Optimisation for Event-based Visual Odometry

Event cameras open up new possibilities for robotic perception due to th...

5 Daqi Liu, et al. ∙

research

∙ 01/28/2022

You Only Cut Once: Boosting Data Augmentation with a Single Cut

We present You Only Cut Once (YOCO) for performing data augmentations. Y...

23 Junlin Han, et al. ∙

research

∙ 10/22/2021

PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels

The most competitive noisy label learning methods rely on an unsupervise...

10 Filipe R. Cordeiro, et al. ∙

research

∙ 10/21/2021

Weakly Supervised Training of Monocular 3D Object Detectors Using Wide Baseline Multi-view Traffic Camera Data

Accurate 7DoF prediction of vehicles at an intersection is an important ...

1 Matthew Howe, et al. ∙

research

∙ 09/27/2021

Robotic Vision for Space Mining

Future Moon bases will likely be constructed using resources mined from ...

0 Ragav Sachdeva, et al. ∙

research

∙ 08/23/2021

ODAM: Object Detection, Association, and Mapping using Posed RGB Video

Localizing objects and estimating their extent in 3D is an important ste...

9 Kejie Li, et al. ∙

research

∙ 06/16/2021

JRDB-Act: A Large-scale Multi-modal Dataset for Spatio-temporal Action, Social Group and Activity Detection

The availability of large-scale video action understanding datasets has ...

0 Mahsa Ehsanpour, et al. ∙

research

∙ 05/25/2021

Unsupervised Scale-consistent Depth Learning from Video

We propose a monocular depth estimator SC-Depth, which requires only unl...

17 Jia-Wang Bian, et al. ∙

research

∙ 03/21/2021

ScanMix: Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised Learning

In this paper, we address the problem of training deep neural networks i...

4 Ragav Sachdeva, et al. ∙

research

∙ 03/15/2021

Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging

Under mild conditions on the noise level of the measurements, rotation a...

0 Alvaro Parra, et al. ∙

research

∙ 03/06/2021

LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment

Deep neural network models are robust to a limited amount of label noise...

18 Filipe R. Cordeiro, et al. ∙

research

∙ 03/06/2021

Noisy Label Learning for Large-scale Medical Image Classification

The classification accuracy of deep learning models depends not only on ...

15 Fengbei Liu, et al. ∙

research

∙ 03/05/2021

Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification

The training of deep learning models generally requires a large amount o...

9 Fengbei Liu, et al. ∙

research

∙ 03/01/2021

DF-VO: What Should Be Learnt for Visual Odometry?

Multi-view geometry-based methods dominate the last few decades in monoc...

18 Huangying Zhan, 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...

0 Sourav Garg, et al. ∙

research

∙ 12/09/2020

MO-LTR: Multiple Object Localization, Tracking, and Reconstruction from Monocular RGB Videos

Semantic aware reconstruction is more advantageous than geometric-only r...

0 Kejie Li, et al. ∙

research

∙ 11/11/2020

EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels

The efficacy of deep learning depends on large-scale data sets that have...

6 Ragav Sachdeva, et al. ∙

research

∙ 11/01/2020

HM4: Hidden Markov Model with Memory Management for Visual Place Recognition

Visual place recognition needs to be robust against appearance variabili...

0 Anh-Dzung Doan, et al. ∙

research

∙ 10/15/2020

MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking

Standardized benchmarks have been crucial in pushing the performance of ...

4 Patrick Dendorfer, et al. ∙

research

∙ 08/08/2020

How Trustworthy are the Existing Performance Evaluations for Basic Vision Tasks?

Performance evaluation is indispensable to the advancement of machine vi...

3 Hamid Rezatofighi, et al. ∙

research

∙ 07/06/2020

Joint learning of Social Groups, Individuals Action and Sub-group Activities in Videos

The state-of-the art solutions for human activity understanding from a v...

4 Mahsa Ehsanpour, et al. ∙

research

∙ 06/04/2020

Unsupervised Depth Learning in Challenging Indoor Video: Weak Rectification to Rescue

Single-view depth estimation using CNNs trained from unlabelled videos h...

0 Jia-Wang Bian, et al. ∙

research

∙ 05/11/2020

FroDO: From Detections to 3D Objects

Object-oriented maps are important for scene understanding since they jo...

0 Kejie Li, et al. ∙

research

∙ 03/19/2020

MOT20: A benchmark for multi object tracking in crowded scenes

Standardized benchmarks are crucial for the majority of computer vision ...

17 Patrick Dendorfer, et al. ∙

research

∙ 03/17/2020

Real-time Image Smoothing via Iterative Least Squares

Edge-preserving image smoothing is a fundamental procedure for many comp...

0 Wei Liu, et al. ∙

research

∙ 02/17/2020

3D Gated Recurrent Fusion for Semantic Scene Completion

This paper tackles the problem of data fusion in the semantic scene comp...

0 Yu Liu, et al. ∙

research

∙ 02/11/2020

Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning

Hyperspectral image(HSI) classification has been improved with convoluti...

0 Haokui Zhang, et al. ∙

research

∙ 02/07/2020

Switchable Precision Neural Networks

Instantaneous and on demand accuracy-efficiency trade-off has been recen...

3 Luis Guerra, et al. ∙

research

∙ 02/03/2020

Automatic Pruning for Quantized Neural Networks

Neural network quantization and pruning are two techniques commonly used...

4 Luis Guerra, et al. ∙

research

∙ 01/30/2020

Learn to Predict Sets Using Feed-Forward Neural Networks

This paper addresses the task of set prediction using deep feed-forward ...

30 Hamid Rezatofighi, et al. ∙

research

∙ 01/29/2020

Depth Based Semantic Scene Completion with Position Importance Aware Loss

Semantic Scene Completion (SSC) refers to the task of inferring the 3D s...

14 Yu Liu, et al. ∙

research

∙ 12/10/2019

Learning to generate new indoor scenes

Deep generative models have been used in recent years to learn coherent ...

16 Pulak Purkait, et al. ∙

research

∙ 12/10/2019

NeuRoRA: Neural Robust Rotation Averaging

Multiple rotation averaging is an essential task for structure from moti...

27 Pulak Purkait, et al. ∙

research

∙ 11/07/2019

Improved Visual Localization via Graph Smoothing

Vision based localization is the problem of inferring the pose of the ca...

0 Carlos Lassance, et al. ∙

research

∙ 09/28/2019

Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation

This paper tackles the problem of video object segmentation. We are spec...

29 Yu Liu, et al. ∙

research

∙ 09/22/2019

Structured Binary Neural Networks for Image Recognition

We propose methods to train convolutional neural networks (CNNs) with bo...

0 Bohan Zhuang, et al. ∙

research

∙ 09/21/2019

Visual Odometry Revisited: What Should Be Learnt?

In this work we present a monocular visual odometry (VO) algorithm which...

0 Huangying Zhan, et al. ∙

research

∙ 08/28/2019

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

Recent work has shown that CNN-based depth and ego-motion estimators can...

1 Jia-Wang Bian, et al. ∙

research

∙ 08/26/2019

An Evaluation of Feature Matchers forFundamental Matrix Estimation

Matching two images while estimating their relative geometry is a key st...

12 Jia-Wang Bian, et al. ∙

research

∙ 08/19/2019

In defense of OSVOS

As a milestone for video object segmentation, one-shot video object segm...

7 Yu Liu, et al. ∙

research

∙ 08/10/2019

Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations

This paper tackles the problem of training a deep convolutional neural n...

0 Bohan Zhuang, et al. ∙

research

∙ 08/01/2019

Scalable Place Recognition Under Appearance Change for Autonomous Driving

A major challenge in place recognition for autonomous driving is to be r...

0 Anh-Dzung Doan, et al. ∙

Ian Reid

Featured Co-authors