Papers › ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization

ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization

14 Sep 2016arXiv:1609.04331archive 2025-07-28

Vadim Kantorov, Maxime Oquab, Minsu Cho, Ivan Laptev

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 precise object boundaries. We address this problem by introducing two types of context-aware guidance models, additive and contrastive models, that leverage their surrounding context regions to improve localization. The additive model encourages the predicted object region to be supported by its surrounding context region. The contrastive model encourages the predicted object region to be outstanding from its surrounding context region. Our approach benefits from the recent success of convolutional neural networks for object recognition and extends Fast R-CNN to weakly supervised object localization. Extensive experimental evaluation on the PASCAL VOC 2007 and 2012 benchmarks shows hat our context-aware approach significantly improves weakly supervised localization and detection.

PaperPDFCode

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

Code

vadimkantorov/contextlocnet mentioned on GitHubtorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

ObjectObject LocalizationObject RecognitionWeakly Supervised Object DetectionWeakly-Supervised Object Localization

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Weakly Supervised Object Detection Charades ContextLocNet MAP 1.12 #4 of 6 Archive leaderboard report
Weakly Supervised Object Detection PASCAL VOC 2007 WSDDN + context MAP 36.3 #39 of 41 Archive leaderboard report
Weakly Supervised Object Detection PASCAL VOC 2012 test WSDDN + context MAP 35.3 #31 of 32 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

ConvolutionFast R-CNNRoIPoolSoftmax

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections