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Found 5 papers, 2 papers with code
Adaptive Density Estimation for Generative Models
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.
Coverage and Quality Driven Training of Generative Image Models
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?
Generative adversarial networks (GANs) are one of the most popular methods for generating images today.
Incremental Learning of Object Detectors without Catastrophic Forgetting
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.
BlitzNet: A Real-Time Deep Network for Scene Understanding
Real-time scene understanding has become crucial in many applications such as autonomous driving.
Ranked #2 on
Real-Time Object Detection
on PASCAL VOC 2007
