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20142022
most citedLearning What and Where to Draw

210 citations · 667 across the 17 of their papers we have counts for

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18 papers · 1 filter

cs.CV2022

Discovering Class-Specific GAN Controls for Semantic Image Synthesis

Edgar Schönfeld, Julio Borges, Vadim Sushko +2

Prior work has extensively studied the latent space structure of GANs for unconditional image synthesis, enabling global editing of generated images by the unsupervised discovery o…

cs.CV20225 cited

Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts

Qi Fan, Mattia Segu, Yu-Wing Tai +4

Improving model's generalizability against domain shifts is crucial, especially for safety-critical applications such as autonomous driving. Real-world domain styles can vary subst…

cs.CV20214 cited

Keypoint Message Passing for Video-based Person Re-Identification

Di Chen, Andreas Doering, Shanshan Zhang +3

Video-based person re-identification (re-ID) is an important technique in visual surveillance systems which aims to match video snippets of people captured by different cameras. Ex…

cs.CV20213 cited

Revisiting Consistency Regularization for Semi-Supervised Learning

Yue Fan, Anna Kukleva, Bernt Schiele

Consistency regularization is one of the most widely-used techniques for semi-supervised learning (SSL). Generally, the aim is to train a model that is invariant to various data au…

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…