temporal-shift-module
Temporal processor
Develops a video analysis module with efficient temporal processing capabilities
[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
2k stars
42 watching
416 forks
Language: Python
last commit: 8 months ago accelerationefficient-modellow-latencynvidia-jetson-nanotemporal-modelingtsmvideo-understanding
Related projects:
| Repository | Description | Stars |
|---|---|---|
 llyx97/tempcompass | A tool to evaluate video language models' ability to understand and describe video content | 91 |
 predict-idlab/tsflex | A toolkit for flexible time series processing and feature extraction. | 405 |
 yjxiong/tsn-pytorch | A PyTorch implementation of Temporal Segment Networks (TSN) for action recognition and video understanding. | 1,066 |
 zygurt/tsm | Tools and methods for modifying the timing of audio signals in various ways | 62 |
 researchmm/sttn | Proposes a deep learning model to fill missing regions in video frames and generate completed videos | 480 |
 labatrockwell/opentsps | A toolkit for analyzing live video and sending the results in various formats to clients. | 194 |
 torchspatiotemporal/tsl | A comprehensive library for processing spatiotemporal data with PyTorch | 281 |
 machine-w/crown | A lightweight ORM library for TDengine time series databases | 35 |
 mysteryx93/hanumaninstituteapps | A suite of tools for audio and video processing, including pitch-shifting, batch conversion, and background playback. | 144 |
 fzj-iek3-vsa/tsam | A Python package for aggregating and analyzing time series data to accelerate model runs | 150 |
 viorik/convlstm | An implementation of a spatio-temporal convolutional LSTM module for video autoencoders with differentiable memory | 293 |
 fabian-jung/tsmp | Tool to generate meta-programming capabilities from source code analysis | 97 |
 jordipons/icassp2017 | Designs efficient architectures for modeling temporal features with deep learning networks | 16 |
 zhegan27/tsbn_code_nips2015 | This Matlab code implements a deep learning model for sequence modeling using a novel belief network architecture. | 48 |
 techascent/tech.ml.dataset | A Clojure library for efficient tabular data processing and analysis | 687 |