Search Results for author: Huy V. Vo

Found 8 papers, 7 papers with code

Active Learning Strategies for Weakly-supervised Object Detection

1 code implementation25 Jul 2022 Huy V. Vo, Oriane Siméoni, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Jean Ponce

On COCO, using on average 10 fully-annotated images per class, or equivalently 1% of the training set, BiB also reduces the performance gap (in AP) between the weakly-supervised detector and the fully-supervised Fast RCNN by over 70%, showing a good trade-off between performance and data efficiency.

Active Learning Object +1

Localizing Objects with Self-Supervised Transformers and no Labels

2 code implementations29 Sep 2021 Oriane Siméoni, Gilles Puy, Huy V. Vo, Simon Roburin, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Renaud Marlet, Jean Ponce

We also show that training a class-agnostic detector on the discovered objects boosts results by another 7 points.

Ranked #4 on Weakly-Supervised Object Localization on CUB-200-2011 (Top-1 Localization Accuracy metric)

Object Object Discovery +2

Large-Scale Unsupervised Object Discovery

1 code implementation NeurIPS 2021 Huy V. Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez, Jean Ponce

Extensive experiments on COCO and OpenImages show that, in the single-object discovery setting where a single prominent object is sought in each image, the proposed LOD (Large-scale Object Discovery) approach is on par with, or better than the state of the art for medium-scale datasets (up to 120K images), and over 37% better than the only other algorithms capable of scaling up to 1. 7M images.

Multi-object discovery Object +2

Structural inpainting

no code implementations27 Mar 2018 Huy V. Vo, Ngoc Q. K. Duong, Patrick Perez

Scene-agnostic visual inpainting remains very challenging despite progress in patch-based methods.

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