research
∙
08/22/2023
Hey That's Mine Imperceptible Watermarks are Preserved in Diffusion Generated Outputs
Generative models have seen an explosion in popularity with the release ...
share
research
∙
08/21/2023
Long-Term Prediction of Natural Video Sequences with Robust Video Predictors
Predicting high dimensional video sequences is a curiously difficult pro...
research
∙
06/15/2023
Motion Perceiver: Real-Time Occupancy Forecasting for Embedded Systems
This work introduces a flexible architecture for real-time occupancy for...
research
∙
04/05/2023
Knowledge Combination to Learn Rotated Detection Without Rotated Annotation
Rotated bounding boxes drastically reduce output ambiguity of elongated ...
research
∙
11/22/2022
Multimorbidity Content-Based Medical Image Retrieval Using Proxies
Content-based medical image retrieval is an important diagnostic tool th...
research
∙
10/09/2022
A Differentiable Distance Approximation for Fairer Image Classification
Naively trained AI models can be heavily biased. This can be particularl...
research
∙
07/25/2022
Deep Laparoscopic Stereo Matching with Transformers
The self-attention mechanism, successfully employed with the transformer...
research
∙
06/15/2022
Rethinking Generalization in Few-Shot Classification
Single image-level annotations only correctly describe an often small su...
research
∙
06/15/2022
On Enforcing Better Conditioned Meta-Learning for Rapid Few-Shot Adaptation
Inspired by the concept of preconditioning, we propose a novel method to...
research
∙
03/14/2022
Implicit Motion Handling for Video Camouflaged Object Detection
We propose a new video camouflaged object detection (VCOD) framework tha...
research
∙
12/07/2021
Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
Learning and generalizing to novel concepts with few samples (Few-Shot L...
research
∙
12/03/2021
Adaptive Poincaré Point to Set Distance for Few-Shot Classification
Learning and generalizing from limited examples, i,e, few-shot learning,...
research
∙
11/12/2021
Learning Online for Unified Segmentation and Tracking Models
Tracking requires building a discriminative model for the target in the ...
research
∙
04/22/2021
Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition
In the real world, medical datasets often exhibit a long-tailed data dis...
research
∙
04/08/2021
Seeing Thru Walls: Visualizing Mobile Robots in Augmented Reality
We present an approach for visualizing mobile robots through an Augmente...
research
∙
04/07/2021
Demonstrating Cloth Folding to Robots: Design and Evaluation of a 2D and a 3D User Interface
An appropriate user interface to collect human demonstration data for de...
research
∙
03/27/2021
Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers
Tracking a time-varying indefinite number of objects in a video sequence...
research
∙
03/06/2021
Visualizing Robot Intent for Object Handovers with Augmented Reality
Humans are very skillful in communicating their intent for when and wher...
research
∙
02/28/2021
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation
Deep neural networks are known to be data-driven and label noise can hav...
research
∙
11/27/2020
Leveraging Regular Fundus Images for Training UWF Fundus Diagnosis Models via Adversarial Learning and Pseudo-Labeling
Recently, ultra-widefield (UWF) 200-degree fundus imaging by Optos camer...
research
∙
11/09/2020
Localising In Complex Scenes Using Balanced Adversarial Adaptation
Domain adaptation and generative modelling have collectively mitigated t...
research
∙
11/04/2020
Residual Likelihood Forests
This paper presents a novel ensemble learning approach called Residual L...
research
∙
10/26/2020
Hierarchical Neural Architecture Search for Deep Stereo Matching
To reduce the human efforts in neural network design, Neural Architectur...
research
∙
08/10/2020
Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning
Camera-based end-to-end driving neural networks bring the promise of a l...
research
∙
05/02/2020
Supportive Actions for Manipulation in Human-Robot Coworker Teams
The increasing presence of robots alongside humans, such as in human-rob...
research
∙
04/01/2020
Learning to Place Objects onto Flat Surfaces in Human-Preferred Orientations
We study the problem of placing a grasped object on an empty flat surfac...
research
∙
03/23/2020
Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus Images via Adversarial Domain Adaptation
For decades, advances in retinal imaging technology have enabled effecti...
research
∙
03/20/2020
How to Train Your Event Camera Neural Network
Event cameras are paradigm-shifting novel sensors that report asynchrono...
research
∙
03/18/2020
OpenGAN: Open Set Generative Adversarial Networks
Many existing conditional Generative Adversarial Networks (cGANs) are li...
research
∙
02/07/2020
Switchable Precision Neural Networks
Instantaneous and on demand accuracy-efficiency trade-off has been recen...
research
∙
02/03/2020
Automatic Pruning for Quantized Neural Networks
Neural network quantization and pruning are two techniques commonly used...
research
∙
10/11/2019
Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation
Recent works show that Generative Adversarial Networks (GANs) can be suc...
research
∙
07/31/2019
EMPNet: Neural Localisation and Mapping using Embedded Memory Points
Continuously estimating an agent's state space and a representation of i...
research
∙
06/17/2019
Embracing Contact: Pushing Multiple Objects with Robot's Forearm
Grasping is the dominant approach for robot manipulation, but only a sin...
research
∙
05/22/2019
Practical Robot Learning from Demonstrations using Deep End-to-End Training
Robots need to learn behaviors in intuitive and practical ways for wides...
research
∙
04/11/2019
Learning to Take Good Pictures of People with a Robot Photographer
We present a robotic system capable of navigating autonomously by follow...
research
∙
04/02/2019
Event-Based Motion Segmentation by Motion Compensation
In contrast to traditional cameras, whose pixels have a common exposure ...
research
∙
02/27/2019
The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning
State-of-the-art deep neural network recognition systems are designed fo...
research
∙
02/20/2019
Look No Deeper: Recognizing Places from Opposing Viewpoints under Varying Scene Appearance using Single-View Depth Estimation
Visual place recognition (VPR) - the act of recognizing a familiar visua...
research
∙
12/06/2018
Traversing Latent Space using Decision Ferns
The practice of transforming raw data to a feature space so that inferen...
research
∙
10/16/2018
Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks
In this paper, we introduce a novel methodology for characterising the p...
research
∙
09/13/2018
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
Deployment of deep learning models in robotics as sensory information ex...
research
∙
07/24/2018
CReaM: Condensed Real-time Models for Depth Prediction using Convolutional Neural Networks
Since the resurgence of CNNs the robotic vision community has developed ...
research
∙
07/16/2018
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs
Recovering structure and motion parameters given a image pair or a seque...
research
∙
06/30/2018
Quantity beats quality for semantic segmentation of corrosion in images
Dataset creation is typically one of the first steps when applying Artif...
research
∙
05/31/2018
Learning Factorized Representations for Open-set Domain Adaptation
Domain adaptation for visual recognition has undergone great progress in...
research
∙
05/14/2018
Generative Adversarial Forests for Better Conditioned Adversarial Learning
In recent times, many of the breakthroughs in various vision-related tas...
research
∙
05/11/2018
Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View Depth Predictors as Priors
We present "just-in-time reconstruction" as real-time image-guided inpai...
research
∙
04/28/2018
Efficient Subpixel Refinement with Symbolic Linear Predictors
We present an efficient subpixel refinement method usinga learning-based...
research
∙
07/03/2017