Deep Ensembles for free through Data Augmentations: TBA

DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation

Driven by arguments from information theory, we introduce a new learning strategy for deep ensembles that increases diversity among members: we adversarially prevent features from being conditionally redundant.

CORE: Color Regression for Multiple Colors Fashion Garments

We detect continuous colors for fashion garments using a new architecture.

OMNIA Faster R-CNN: Detection in the Wild through Dataset Merging and Soft Distillation

We improve performances of object detectors via combining different datasets through soft distillation.

Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction

We present a method to learn a visual representation adapted for e-commerce products.



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Deep Learning for Computer Vision
Deep Learning