TIC Detection

TIC detection encompasses two distinct research areas: automatic detection of motor tics in video for aiding Tourette Syndrome treatment, and text-guided image colorization. Current research in tic detection for TS focuses on developing robust and interpretable deep learning models capable of analyzing untrimmed video footage to identify and classify tics, improving the accessibility of behavioral therapy. In image colorization, researchers are exploring the use of textual descriptions as conditioning information to enhance the realism and accuracy of colorization algorithms, leveraging deep neural networks for improved performance. These advancements have the potential to significantly improve both clinical practice and computer vision applications.