79 citations · 608 across the 98 of their papers we have counts for
7 papers · 2 filters
3D Trajectory Reconstruction of Dynamic Objects Using Planarity Constraints
Sebastian Bullinger, Christoph Bodensteiner, Michael Arens +1
We present a method to reconstruct the three-dimensional trajectory of a moving instance of a known object category in monocular video data. We track the two-dimensional shape of o…
A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking
M. Saquib Sarfraz, Arne Schumann, Andreas Eberle +1
Person re identification is a challenging retrieval task that requires matching a person's acquired image across non overlapping camera views. In this paper we propose an effective…
Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks
Ali Diba, Vivek Sharma, Rainer Stiefelhagen +1
The deep generative adversarial networks (GAN) recently have been shown to be promising for different computer vision applications, like image edit- ing, synthesizing high resoluti…
Classification Driven Dynamic Image Enhancement
Vivek Sharma, Ali Diba, Davy Neven +3
Convolutional neural networks rely on image texture and structure to serve as discriminative features to classify the image content. Image enhancement techniques can be used as pre…
Deep View-Sensitive Pedestrian Attribute Inference in an end-to-end Model
M. Saquib Sarfraz, Arne Schumann, Yan Wang +1
Pedestrian attribute inference is a demanding problem in visual surveillance that can facilitate person retrieval, search and indexing. To exploit semantic relations between attrib…
Fashion Forward: Forecasting Visual Style in Fashion
Ziad Al-Halah, Rainer Stiefelhagen, Kristen Grauman
What is the future of fashion? Tackling this question from a data-driven vision perspective, we propose to forecast visual style trends before they occur. We introduce the first ap…
Automatic Discovery, Association Estimation and Learning of Semantic Attributes for a Thousand Categories
Ziad Al-Halah, Rainer Stiefelhagen
Attribute-based recognition models, due to their impressive performance and their ability to generalize well on novel categories, have been widely adopted for many computer vision…