266 citations · 493 across the 37 of their papers we have counts for
7 papers · 1 filter
Improving Object Localization with Fitness NMS and Bounded IoU Loss
Lachlan Tychsen-Smith, Lars Petersson
We demonstrate that many detection methods are designed to identify only a sufficently accurate bounding box, rather than the best available one. To address this issue we propose a…
Soft Correspondences in Multimodal Scene Parsing
Sarah Taghavi Namin, Mohammad Najafi, Mathieu Salzmann +1
Exploiting multiple modalities for semantic scene parsing has been shown to improve accuracy over the singlemodality scenario. However multimodal datasets often suffer from problem…
Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Correspondence
Dylan Campbell, Lars Petersson, Laurent Kneip +1
Estimating the 6-DoF pose of a camera from a single image relative to a pre-computed 3D point-set is an important task for many computer vision applications. Perspective-n-Point (P…
Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation
Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann +2
Pixel-level annotations are expensive and time-consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recent y…
Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation
Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann +3
Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently…
DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling
Lachlan Tychsen-Smith, Lars Petersson
We define the object detection from imagery problem as estimating a very large but extremely sparse bounding box dependent probability distribution. Subsequently we identify a spar…