Search Results for author: Konstantin Shmelkov

Found 5 papers, 2 papers with code

Adaptive Density Estimation for Generative Models

no code implementations NeurIPS 2019 Thomas Lucas, Konstantin Shmelkov, Karteek Alahari, Cordelia Schmid, Jakob Verbeek

We show that our model significantly improves over existing hybrid models: offering GAN-like samples, IS and FID scores that are competitive with fully adversarial models, and improved likelihood scores.

Density Estimation

Coverage and Quality Driven Training of Generative Image Models

no code implementations27 Sep 2018 Thomas Lucas, Konstantin Shmelkov, Karteek Alahari, Cordelia Schmid, Jakob Verbeek

First, we propose a model that extends variational autoencoders by using deterministic invertible transformation layers to map samples from the decoder to the image space.

How good is my GAN?

no code implementations ECCV 2018 Konstantin Shmelkov, Cordelia Schmid, Karteek Alahari

Generative adversarial networks (GANs) are one of the most popular methods for generating images today.

General Classification Image Classification +1

Incremental Learning of Object Detectors without Catastrophic Forgetting

3 code implementations ICCV 2017 Konstantin Shmelkov, Cordelia Schmid, Karteek Alahari

Despite their success for object detection, convolutional neural networks are ill-equipped for incremental learning, i. e., adapting the original model trained on a set of classes to additionally detect objects of new classes, in the absence of the initial training data.

Incremental Learning Object +2

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