딥러닝 공부방

Unsupervised Learning of Visual Representations using Videos Xiaolong Wang, Abhinav Gupta, arXiv 2015 PDF, Video By SeonghoonYu July 23th, 2021 Summary This paper use hundreds of thousands of unlabeled videos from the web to learn visual representations. They use the first frame and the last frame in same video as positive samples and a random frame from different video as negative sample. They ..

TSM: Temporal Shift Module for Efficient Video Understanding Ji Lin, Chuang Gan, Song Han, arXiv 2018 PDF Video By SeonghoonYu July 23th, 2021 Summary This paper is 2D Conv based Video model. They present TSM(temporal shift Module). It can be inserted into 2D CNNs to achieve temporal modeling at zero computation and zero parameters. TSM shift the channels along the temporal dimension both forwar..

SlowFast Networks for Video Recognition Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, Kaiming He, arXiv 2018 PDF, Video By SeonghoonYu July 20th, 2021 Summary They presents a two-pathway SlowFast model for video recognition. Two pathways seperately work at low and high temporal resolutions. (1) One is Slow pathway designed to capture sementic information that can be given by a few sparse f..

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset Joao Carreira, Andrew Zisserman, arXiv 2017 PDF, VD By SeonghoonYu July 17th, 2021 Summary They achive SOTA performence in video action recognition using two method. (1) Apply ImageNet pre-trained 2D Conv model to 3D Conv model for the video classification by repeating the weights of the 2D filters N times along the time dimensi..