97 citations · 136 across the 10 of their papers we have counts for
5 papers · 1 filter
CoRe: Color Regression for Multicolor Fashion Garments
Alexandre Rame, Arthur Douillard, Charles Ollion
Developing deep networks that analyze fashion garments has many real-world applications. Among all fashion attributes, color is one of the most important yet challenging to detect.…
Insights from the Future for Continual Learning
Arthur Douillard, Eduardo Valle, Charles Ollion +2
Continual learning aims to learn tasks sequentially, with (often severe) constraints on the storage of old learning samples, without suffering from catastrophic forgetting. In this…
PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning
Arthur Douillard, Matthieu Cord, Charles Ollion +2
Lifelong learning has attracted much attention, but existing works still struggle to fight catastrophic forgetting and accumulate knowledge over long stretches of incremental learn…
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation
Alexandre Rame, Emilien Garreau, Hedi Ben-Younes +1
Object detectors tend to perform poorly in new or open domains, and require exhaustive yet costly annotations from fully labeled datasets. We aim at benefiting from several dataset…
Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction
Charles Corbière, Hedi Ben-Younes, Alexandre Ramé +1
In this paper, we present a method to learn a visual representation adapted for e-commerce products. Based on weakly supervised learning, our model learns from noisy datasets crawl…