conifer
Fast inference of Boosted Decision Trees in FPGAs (by thesps)
temporal-shift-module
[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding (by mit-han-lab)
| conifer | temporal-shift-module | |
|---|---|---|
| 1 | 3 | |
| 40 | 2,018 | |
| - | 0.4% | |
| 6.9 | 3.0 | |
| 3 months ago | 7 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
conifer
Posts with mentions or reviews of conifer.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Random Forest: how are predictions related to node values?
I came across a useful package ( https://github.com/thesps/conifer), but it does not support multiclass classification for RF.
temporal-shift-module
Posts with mentions or reviews of temporal-shift-module.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-11-21.
- Stable Video Diffusion
-
Can two-stream networks trained for video action recognition be used for real-time usecases?
My question mostly has to do with optical flow. One of the two-stream networks I'm interested in trying out is TSN-TSM, as there are pre-trained weights available for it on the Assembly101 dataset released a few months ago.
-
I am having a hard time understanding this paper(Temporal shift module). Can some who have read it before or willing to read it explain me better in a more elaborate way?
This is the paper. (https://arxiv.org/abs/1811.08383). Here they are talking about how they can achieve temporal modelling by moving channels, which I assume are the RGB channels across frames. But I am super confused by the lingo. Here is the repo (https://github.com/mit-han-lab/temporal-shift-module). I can't give better rewards except virtual hugs. Thank you.
What are some alternatives?
When comparing conifer and temporal-shift-module you can also consider the following projects:
python-socketio - Python Socket.IO server and client
mmaction2 - OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
fusesoc - Package manager and build abstraction tool for FPGA/ASIC development
qkeras - QKeras: a quantization deep learning library for Tensorflow Keras
react-native-sensors - A developer friendly approach for sensors in React Native
conifer - Collect and revisit web pages.
gsgen - [CVPR 2024] Text-to-3D using Gaussian Splatting
generative-models - Generative Models by Stability AI
S2-BNN - S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
civitai - A repository of models, textual inversions, and more
instruct-pix2pix
conifer vs python-socketio
temporal-shift-module vs mmaction2
conifer vs fusesoc
temporal-shift-module vs python-socketio
conifer vs qkeras
temporal-shift-module vs react-native-sensors
temporal-shift-module vs conifer
temporal-shift-module vs gsgen
temporal-shift-module vs generative-models
temporal-shift-module vs S2-BNN
temporal-shift-module vs civitai
temporal-shift-module vs instruct-pix2pix