research
∙
07/20/2023
Kick Back Relax: Learning to Reconstruct the World by Watching SlowTV
Self-supervised monocular depth estimation (SS-MDE) has the potential to...
share
research
∙
04/14/2023
The Second Monocular Depth Estimation Challenge
This paper discusses the results for the second edition of the Monocular...
research
∙
02/15/2023
CERiL: Continuous Event-based Reinforcement Learning
This paper explores the potential of event cameras to enable continuous ...
research
∙
11/22/2022
The Monocular Depth Estimation Challenge
This paper summarizes the results of the first Monocular Depth Estimatio...
research
∙
11/14/2022
SVS: Adversarial refinement for sparse novel view synthesis
This paper proposes Sparse View Synthesis. This is a view synthesis prob...
research
∙
09/09/2022
EDeNN: Event Decay Neural Networks for low latency vision
Despite the success of neural networks in computer vision tasks, digital...
research
∙
08/02/2022
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that Matter
This paper presents an open and comprehensive framework to systematicall...
research
∙
07/27/2022
Adaptive sampling for scanning pixel cameras
A scanning pixel camera is a novel low-cost, low-power sensor that is no...
research
∙
05/16/2022
Generalizing to New Tasks via One-Shot Compositional Subgoals
The ability to generalize to previously unseen tasks with little to no s...
research
∙
05/14/2022
SaiNet: Stereo aware inpainting behind objects with generative networks
In this work, we present an end-to-end network for stereo-consistent ima...
research
∙
05/06/2022
SKILL-IL: Disentangling Skill and Knowledge in Multitask Imitation Learning
In this work, we introduce a new perspective for learning transferable c...
research
∙
04/12/2022
Medusa: Universal Feature Learning via Attentional Multitasking
Recent approaches to multi-task learning (MTL) have focused on modelling...
research
∙
10/25/2021
SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition
We present SILT, a Self-supervised Implicit Lighting Transfer method. Un...
research
∙
09/22/2021
TACTIC: Joint Rate-Distortion-Accuracy Optimisation for Low Bitrate Compression
We present TACTIC: Task-Aware Compression Through Intelligent Coding. Ou...
research
∙
09/01/2021
EVReflex: Dense Time-to-Impact Prediction for Event-based Obstacle Avoidance
The broad scope of obstacle avoidance has led to many kinds of computer ...
research
∙
06/02/2021
Robot in a China Shop: Using Reinforcement Learning for Location-Specific Navigation Behaviour
Robots need to be able to work in multiple different environments. Even ...
research
∙
06/01/2021
Markov Localisation using Heatmap Regression and Deep Convolutional Odometry
In the context of self-driving vehicles there is strong competition betw...
research
∙
03/17/2021
A Robust Extrinsic Calibration Framework for Vehicles with Unscaled Sensors
Accurate extrinsic sensor calibration is essential for both autonomous v...
research
∙
11/10/2020
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes
We present a novel form of explanation for Reinforcement Learning, based...
research
∙
10/04/2020
Diagonal Memory Optimisation for Machine Learning on Micro-controllers
As machine learning spreads into more and more application areas, micro ...
research
∙
09/01/2020
Multi-channel Transformers for Multi-articulatory Sign Language Translation
Sign languages use multiple asynchronous information channels (articulat...
research
∙
03/30/2020
Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation
Prior work on Sign Language Translation has shown that having a mid-leve...
research
∙
03/30/2020
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning
In the current monocular depth research, the dominant approach is to emp...
research
∙
03/30/2020
Same Features, Different Day: Weakly Supervised Feature Learning for Seasonal Invariance
"Like night and day" is a commonly used expression to imply that two thi...
research
∙
03/25/2019
Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation
How do computers and intelligent agents view the world around them? Feat...
research
∙
11/19/2018
Localisation via Deep Imagination: learn the features not the map
How many times does a human have to drive through the same area to becom...
research
∙
09/05/2017