176 citations · 538 across the 62 of their papers we have counts for
21 papers · 1 filter
SSLR: A Semi-Supervised Learning Method for Isolated Sign Language Recognition
Hasan Algafri, Hamzah Luqman, Sarah Alyami +1
Sign language is the primary communication language for people with disabling hearing loss. Sign language recognition (SLR) systems aim to recognize sign gestures and translate the…
StarVector: Generating Scalable Vector Graphics Code from Images and Text
Juan A. Rodriguez, Abhay Puri, Shubham Agarwal +6
Scalable Vector Graphics (SVGs) are vital for modern image rendering due to their scalability and versatility. Previous SVG generation methods have focused on curve-based vectoriza…
Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images
Saypraseuth Mounsaveng, Issam Laradji, David Vázquez +2
Training a deep learning model to classify histopathological images is challenging, because of the color and shape variability of the cells and tissues, and the reduced amount of a…
FigGen: Text to Scientific Figure Generation
Juan A Rodriguez, David Vazquez, Issam Laradji +2
The generative modeling landscape has experienced tremendous growth in recent years, particularly in generating natural images and art. Recent techniques have shown impressive pote…
OCR-VQGAN: Taming Text-within-Image Generation
Juan A. Rodriguez, David Vazquez, Issam Laradji +2
Synthetic image generation has recently experienced significant improvements in domains such as natural image or art generation. However, the problem of figure and diagram generati…
Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer +32
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and trainin…
Neural Point Light Fields
Julian Ost, Issam Laradji, Alejandro Newell +2
We introduce Neural Point Light Fields that represent scenes implicitly with a light field living on a sparse point cloud. Combining differentiable volume rendering with learned im…
A Survey of Self-Supervised and Few-Shot Object Detection
Gabriel Huang, Issam Laradji, David Vazquez +2
Labeling data is often expensive and time-consuming, especially for tasks such as object detection and instance segmentation, which require dense labeling of the image. While few-s…
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction
Issam Laradji, Pau Rodríguez, David Vazquez +1
Recent work has made significant progress in learning object meshes with weak supervision. Soft Rasterization methods have achieved accurate 3D reconstruction from 2D images with v…
Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery
Issam Laradji, Pau Rodriguez, Freddie Kalaitzis +4
Cattle farming is responsible for 8.8\% of greenhouse gas emissions worldwide. In addition to the methane emitted due to their digestive process, the growing need for grazing areas…
Affinity LCFCN: Learning to Segment Fish with Weak Supervision
Issam Laradji, Alzayat Saleh, Pau Rodriguez +3
Aquaculture industries rely on the availability of accurate fish body measurements, e.g., length, width and mass. Manual methods that rely on physical tools like rulers are time an…
CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions
Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodriguez +12
In the last few years, we have witnessed a renewed and fast-growing interest in continual learning with deep neural networks with the shared objective of making current AI systems…
Synbols: Probing Learning Algorithms with Synthetic Datasets
Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron +7
Progress in the field of machine learning has been fueled by the introduction of benchmark datasets pushing the limits of existing algorithms. Enabling the design of datasets to te…
A Realistic Fish-Habitat Dataset to Evaluate Algorithms for Underwater Visual Analysis
Alzayat Saleh, Issam H. Laradji, Dmitry A. Konovalov +3
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for human consumption and environmental protection. Deep Learning methods have shown gre…
LOOC: Localize Overlapping Objects with Count Supervision
Issam H. Laradji, Rafael Pardinas, Pau Rodriguez +1
Acquiring count annotations generally requires less human effort than point-level and bounding box annotations. Thus, we propose the novel problem setup of localizing objects in de…
Learning Data Augmentation with Online Bilevel Optimization for Image Classification
Saypraseuth Mounsaveng, Issam Laradji, Ismail Ben Ayed +2
Data augmentation is a key practice in machine learning for improving generalization performance. However, finding the best data augmentation hyperparameters requires domain knowle…
Embedding Propagation: Smoother Manifold for Few-Shot Classification
Pau Rodríguez, Issam Laradji, Alexandre Drouin +1
Few-shot classification is challenging because the data distribution of the training set can be widely different to the test set as their classes are disjoint. This distribution sh…
Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation
Lironne Kurzman, David Vazquez, Issam Laradji
We propose a Class-Based Styling method (CBS) that can map different styles for different object classes in real-time. CBS achieves real-time performance by carrying out two steps…
Where are the Masks: Instance Segmentation with Image-level Supervision
Issam H. Laradji, David Vazquez, Mark Schmidt
A major obstacle in instance segmentation is that existing methods often need many per-pixel labels in order to be effective. These labels require large human effort and for certai…
Instance Segmentation with Point Supervision
Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro +2
Instance segmentation methods often require costly per-pixel labels. We propose a method that only requires point-level annotations. During training, the model only has access to a…
Where are the Blobs: Counting by Localization with Point Supervision
Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro +2
Object counting is an important task in computer vision due to its growing demand in applications such as surveillance, traffic monitoring, and counting everyday objects. State-of-…