activity
20142016
most citedLearning What and Where to Draw

210 citations · 660 across the 14 of their papers we have counts for

collaborators

16 papers

cs.CV20195 cited

A Novel BiLevel Paradigm for Image-to-Image Translation

Liqian Ma, Qianru Sun, Bernt Schiele +1

Image-to-image (I2I) translation is a pixel-level mapping that requires a large number of paired training data and often suffers from the problems of high diversity and strong cate…

cs.CV20191 cited

f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning

Yongqin Xian, Saurabh Sharma, Bernt Schiele +1

When labeled training data is scarce, a promising data augmentation approach is to generate visual features of unknown classes using their attributes. To learn the class conditiona…

cs.CV2016

EgoCap: Egocentric Marker-less Motion Capture with Two Fisheye Cameras (Extended Abstract)

Helge Rhodin, Christian Richardt, Dan Casas +5

Marker-based and marker-less optical skeletal motion-capture methods use an outside-in arrangement of cameras placed around a scene, with viewpoints converging on the center. They…

cs.CV20162 cited

Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel Classification

Maksim Lapin, Matthias Hein, Bernt Schiele

Top-k error is currently a popular performance measure on large scale image classification benchmarks such as ImageNet and Places. Despite its wide acceptance, our understanding of…

cs.CV201615 cited

Joint Graph Decomposition and Node Labeling: Problem, Algorithms, Applications

Evgeny Levinkov, Jonas Uhrig, Siyu Tang +7

We state a combinatorial optimization problem whose feasible solutions define both a decomposition and a node labeling of a given graph. This problem offers a common mathematical a…

cs.CV2016210 cited

Learning What and Where to Draw

Scott Reed, Zeynep Akata, Santosh Mohan +3

Generative Adversarial Networks (GANs) have recently demonstrated the capability to synthesize compelling real-world images, such as room interiors, album covers, manga, faces, bir…