A commonly accepted hypothesis is that models with higher accuracy on
Im...
Large-scale multi-label classification datasets are commonly, and perhap...
In recent years the amounts of personal photos captured increased
signif...
Training a neural network model for recognizing multiple labels associat...
ImageNet-1K serves as the primary dataset for pretraining deep learning
...
Leading methods in the domain of action recognition try to distill
infor...
Realistic use of neural networks often requires adhering to multiple
con...
Pictures of everyday life are inherently multi-label in nature. Hence,
m...
We propose a new method for anomaly detection of human actions. Our meth...
The task of person re-identification (ReID) has attracted growing attent...
This paper introduces a novel optimization method for differential neura...
Automatic methods for Neural Architecture Search (NAS) have been shown t...
This paper deals with the prediction of the memorability of a given imag...
One of the key ingredients for successful optimization of modern CNNs is...
Thanks to their remarkable generative capabilities, GANs have gained gre...
This paper reports on the 2018 PIRM challenge on perceptual super-resolu...
Maintaining natural image statistics is a crucial factor in restoration ...
Feed-forward CNNs trained for image transformation problems rely on loss...
Recent work has shown impressive success in transferring painterly style...
We propose a novel measure for template matching named Deformable Divers...
Have you ever taken a picture only to find out that an unimportant backg...
We introduce RIANN (Ring Intersection Approximate Nearest Neighbor searc...