1 code implementation • 17 Mar 2023 • Ryan Webster, Julien Rabin, Loic Simon, Frederic Jurie
Generative models, such as DALL-E, Midjourney, and Stable Diffusion, have societal implications that extend beyond the field of computer science.
no code implementations • 30 Sep 2022 • Juliette Mattioli, Agnes Delaborde, Souhaiel Khalfaoui, Freddy Lecue, Henri Sohier, Frederic Jurie
This paper reviews the entire engineering process of trustworthy Machine Learning (ML) algorithms designed to equip critical systems with advanced analytics and decision functions.
no code implementations • 2 Aug 2021 • Dennis Conway, Loic Simon, Alexis Lechervy, Frederic Jurie
We find that the addition of a small amount of private data greatly improves the performance of our model, which highlights the limitations of using synthetic data to train machine learning models.
no code implementations • 13 Jul 2021 • Ryan Webster, Julien Rabin, Loic Simon, Frederic Jurie
Recently, generative adversarial networks (GANs) have achieved stunning realism, fooling even human observers.
no code implementations • 27 Mar 2019 • Siddharth Srivastava, Frederic Jurie, Gaurav Sharma
We address the problem of 3D object detection from 2D monocular images in autonomous driving scenarios.
3D Object Detection 3D Object Detection From Monocular Images +4
1 code implementation • CVPR 2019 • Ryan Webster, Julien Rabin, Loic Simon, Frederic Jurie
Using this methodology, this paper shows that overfitting is not detectable in the pure GAN models proposed in the literature, in contrast with those using hybrid adversarial losses, which are amongst the most widely applied generative methods.
no code implementations • CVPR 2017 • Ronan Sicre, Yannis Avrithis, Ewa Kijak, Frederic Jurie
This strategy opens the door to the use of PBM in new applications for which the notion of image categories is irrelevant, such as instance-based image retrieval, for example.
no code implementations • 14 Nov 2016 • Ronan Sicre, Julien Rabin, Yannis Avrithis, Teddy Furon, Frederic Jurie
Part-based image classification consists in representing categories by small sets of discriminative parts upon which a representation of the images is built.
no code implementations • 1 Nov 2016 • Binod Bhattarai, Gaurav Sharma, Frederic Jurie
The challenge addressed in this paper is to design a common universal representation such that a single merged signature is transmitted to the server, whatever be the type and number of features computed by the client, ensuring nonetheless an optimal performance.
no code implementations • CVPR 2016 • Binod Bhattarai, Gaurav Sharma, Frederic Jurie
The experiments clearly demonstrate the scalability and improved performance of the proposed method on the tasks of identity and age based face image retrieval compared to competitive existing methods, on the standard datasets and with the presence of a million distractor face images.
no code implementations • 2 Oct 2015 • Gaurav Sharma, Frederic Jurie
We propose a new image representation for texture categorization and facial analysis, relying on the use of higher-order local differential statistics as features.
no code implementations • 14 Sep 2015 • Gaurav Sharma, Frederic Jurie, Cordelia Schmid
We validate our method on three recent challenging datasets of human attributes and actions.
no code implementations • 13 Mar 2015 • Praveen Kulkarni, Joaquin Zepeda, Frederic Jurie, Patrick Perez, Louis Chevallier
A second variant of our approach that includes the fully connected DCNN layers significantly outperforms Fisher vector schemes and performs comparably to DCNN approaches adapted to Pascal VOC 2007, yet at only a small fraction of the training and testing cost.
1 code implementation • Journal of Visual Communication and Image Representation 2015 • Sebastien Razakarivony, Frederic Jurie
VEDAI is a dataset for Vehicle Detection in Aerial Imagery, provided as a tool to benchmark automatic target recognition algorithms in unconstrained environments.
no code implementations • CVPR 2014 • Winn Voravuthikunchai, Bruno Cremilleux, Frederic Jurie
This paper introduces a novel image representation capturing feature dependencies through the mining of meaningful combinations of visual features.
no code implementations • CVPR 2013 • Gaurav Sharma, Frederic Jurie, Cordelia Schmid
We propose a new model for recognizing human attributes (e. g. wearing a suit, sitting, short hair) and actions (e. g. running, riding a horse) in still images.