Search Results for author:
Found 12 papers, 1 papers with code
A survey of manifold learning and its applications for multimedia
Manifold learning is an emerging research domain of machine learning.
Do the Frankenstein, or how to achieve better out-of-distribution performance with manifold mixing model soup
The standard recipe applied in transfer learning is to finetune a pretrained model on the task-specific dataset with different hyperparameter settings and pick the model with the highest accuracy on the validation dataset.
A real-time algorithm for human action recognition in RGB and thermal video
Monitoring the movement and actions of humans in video in real-time is an important task.
FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level
Learning algorithms for Deep Neural Networks are typically based on supervised end-to-end Stochastic Gradient Descent (SGD) training with error backpropagation (backprop).
A qualitative investigation of optical flow algorithms for video denoising
A good optical flow estimation is crucial in many video analysis and restoration algorithms employed in application fields like media industry, industrial inspection and automotive.
AdaFamily: A family of Adam-like adaptive gradient methods
We propose AdaFamily, a novel method for training deep neural networks.
Some like it tough: Improving model generalization via progressively increasing the training difficulty
In this work, we propose to progressively increase the training difficulty during learning a neural network model via a novel strategy which we call mini-batch trimming.
Detecting speaking persons in video
We present a novel method for detecting speaking persons in video, by extracting facial landmarks with a neural network and analysing these landmarks statistically over time
Hyper360 -- a Next Generation Toolset for Immersive Media
Spherical 360{\deg} video is a novel media format, rapidly becoming adopted in media production and consumption of immersive media.
Automatic cinematography for 360 video
We describe our method for automatic generation of a visually interesting camera path (automatic cinematography)from a 360 video.
OmniTrack: Real-time detection and tracking of objects, text and logos in video
The automatic detection and tracking of general objects (like persons, animals or cars), text and logos in a video is crucial for many video understanding tasks, and usually real-time processing as required.
Adapting Computer Vision Algorithms for Omnidirectional Video
Omnidirectional (360{\deg}) video has got quite popular because it provides a highly immersive viewing experience.
