Explore action recognition, temporal localization, and detection in trimmed and untrimmed videos through this 36-minute lecture by Rui Hou from the University of Central Florida. Dive into topics such as knowledge transfer to novel categories, comparison with semantic attributes, and experimental results on datasets like UCF101 and UCF-Sports. Learn about the pipeline for detecting actions, including the adaptation of Faster R-CNN from 2D to 3D, Tube Proposal Network, and Tube of Interest Max Pooling. Examine video action and object segmentation techniques, including encoder-decoder architectures, 3D Pyramid Pooling, and dilated convolution. Gain insights into the current limitations and future directions of research in this field.