44 citations · 99 across the 5 of their papers we have counts for
5 papers
Deep Metric Learning Beyond Binary Supervision
Sungyeon Kim, Minkyo Seo, Ivan Laptev +2
Metric Learning for visual similarity has mostly adopted binary supervision indicating whether a pair of images are of the same class or not. Such a binary indicator covers only a…
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization
Vadim Kantorov, Maxime Oquab, Minsu Cho +1
We aim to localize objects in images using image-level supervision only. Previous approaches to this problem mainly focus on discriminative object regions and often fail to locate…
Much Ado About Time: Exhaustive Annotation of Temporal Data
Gunnar A. Sigurdsson, Olga Russakovsky, Ali Farhadi +2
Large-scale annotated datasets allow AI systems to learn from and build upon the knowledge of the crowd. Many crowdsourcing techniques have been developed for collecting image anno…
On Pairwise Costs for Network Flow Multi-Object Tracking
Visesh Chari, Simon Lacoste-Julien, Ivan Laptev +1
Multi-object tracking has been recently approached with the min-cost network flow optimization techniques. Such methods simultaneously resolve multiple object tracks in a video and…
Weakly Supervised Action Labeling in Videos Under Ordering Constraints
Piotr Bojanowski, Rémi Lajugie, Francis Bach +4
We are given a set of video clips, each one annotated with an {\em ordered} list of actions, such as "walk" then "sit" then "answer phone" extracted from, for example, the associat…