research
∙
09/07/2023
Context-Aware 3D Object Localization from Single Calibrated Images: A Study of Basketballs
Accurately localizing objects in three dimensions (3D) is crucial for va...
share
research
∙
07/12/2023
On the Importance of Denoising when Learning to Compress Images
Image noise is ubiquitous in photography. However, image noise is not co...
research
∙
05/25/2023
An Experimental Investigation into the Evaluation of Explainability Methods
EXplainable Artificial Intelligence (XAI) aims to help users to grasp th...
research
∙
12/02/2022
Are Straight-Through gradients and Soft-Thresholding all you need for Sparse Training?
Turning the weights to zero when training a neural network helps in redu...
research
∙
11/07/2022
Body Part-Based Representation Learning for Occluded Person Re-Identification
Occluded person re-identification (ReID) is a person retrieval task whic...
research
∙
07/11/2022
Forward Error Correction applied to JPEG-XS codestreams
JPEG-XS offers low complexity image compression for applications with co...
research
∙
05/23/2022
Accelerating the creation of instance segmentation training sets through bounding box annotation
Collecting image annotations remains a significant burden when deploying...
research
∙
04/28/2022
Poly-CAM: High resolution class activation map for convolutional neural networks
The need for Explainable AI is increasing with the development of deep l...
research
∙
03/30/2022
Ball 3D localization from a single calibrated image
Ball 3D localization in team sports has various applications including a...
research
∙
12/01/2021
DeepSportLab: a Unified Framework for Ball Detection, Player Instance Segmentation and Pose Estimation in Team Sports Scenes
This paper presents a unified framework to (i) locate the ball, (ii) pre...
research
∙
11/17/2021
End-to-end optimized image compression with competition of prior distributions
Convolutional autoencoders are now at the forefront of image compression...
research
∙
09/03/2021
Ordinal Pooling
In the framework of convolutional neural networks, downsampling is often...
research
∙
03/11/2021
Intraclass clustering: an implicit learning ability that regularizes DNNs
Several works have shown that the regularization mechanisms underlying d...
research
∙
08/29/2020
Improved anomaly detection by training an autoencoder with skip connections on images corrupted with Stain-shaped noise
In industrial vision, the anomaly detection problem can be addressed wit...
research
∙
08/27/2020
How semantic and geometric information mutually reinforce each other in ToF object localization
We propose a novel approach to localize a 3D object from the intensity a...
research
∙
07/23/2020
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup
This paper considers the task of detecting the ball from a single viewpo...
research
∙
05/18/2020
Adapting JPEG XS gains and priorities to tasks and contents
Most current research in the domain of image compression focuses solely ...
research
∙
07/01/2019
Associative Embedding for Game-Agnostic Team Discrimination
Assigning team labels to players in a sport game is not a trivial task w...
research
∙
06/01/2019
Natural Image Noise Dataset
Convolutional neural networks have been the focus of research aiming to ...
research
∙
06/05/2018
On layer-level control of DNN training and its impact on generalization
The generalization ability of a neural network depends on the optimizati...
research
∙
04/13/2018
O-HAZE: a dehazing benchmark with real hazy and haze-free outdoor images
Haze removal or dehazing is a challenging ill-posed problem that has dra...
research
∙
04/13/2018
I-HAZE: a dehazing benchmark with real hazy and haze-free indoor images
Image dehazing has become an important computational imaging topic in th...
research
∙
02/17/2016
Cell segmentation with random ferns and graph-cuts
The progress in imaging techniques have allowed the study of various asp...
research
∙
09/01/2015
Iterative hypothesis testing for multi-object tracking in presence of features with variable reliability
This paper assumes prior detections of multiple targets at each time ins...
research
∙
04/05/2015
Discriminative and Efficient Label Propagation on Complementary Graphs for Multi-Object Tracking
Given a set of detections, detected at each time instant independently, ...
research
∙
09/04/2012
Compressive Optical Deflectometric Tomography: A Constrained Total-Variation Minimization Approach
Optical Deflectometric Tomography (ODT) provides an accurate characteriz...
research
∙
09/15/2010