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Video-Swin-Transformer Alternatives
Similar projects and alternatives to Video-Swin-Transformer
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Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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EconomicTracker
Download data from the Opportunity Insights Economic Tracker — https://tracktherecovery.org/
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Swin-Transformer-Object-Detection
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
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Swin-Transformer-Tensorflow
Unofficial implementation of "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" (https://arxiv.org/abs/2103.14030)
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MoViNet-pytorch
MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;
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Swin-Transformer-Semantic-Segmentation
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Video-Swin-Transformer alternative or higher similarity.
Video-Swin-Transformer reviews and mentions
Posts with mentions or reviews of Video-Swin-Transformer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-02-23.
- Explanation needed
- Explanation needed [P]
- Explanation needed [R]
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Weekly Entering & Transitioning Thread | 20 Feb 2022 - 27 Feb 2022
PROBLEM STATEMENT Develop an efficient common strategy and relevant implementation to extract the video-based models in the black box and grey box setting across the following 2 problem statements. 1.Action Classification Model Extraction for Swin-T Model for Action Classification on Kinetics-400 dataset. Download the model from here- https://github.com/SwinTransformer/Video-Swin-Transformer 2.Video Classification Model Extraction for MoViNet-A2-Base Model for Video Classification on Kinetics- 600 dataset Download the model from here- https://tfhub.dev/tensorflow/movinet/a2/base/kinetics-600/classification/3 Blackbox Setting Do not use any relevant data set available and use synthetic or generated data without using the Kinetics series dataset. Also, do not use the same model architecture as the original model to train the extracted model. Greybox Setting You can use 5% of original data (balanced representation of classes) as a starting point to generate the attack dataset. Also, do not use the same model architecture as the original model to train the extracted model. Can someone explain the problem statement in a easy / understandable way ?? What I think is the models have already been provided and we have to do something in Blackbox and greybox . Can someone explain in brief what we have to do in the blackbox / greybox??
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Action recognition models for images
There are two main variants for the SWIN transformer the original SWIN transformer, official implementation here, and the Video SWIN transformer, official implementation here. Both architectures are very similar with the differences being mainly in the size of the input. The SWIN transformer pretrained on imagenet can be used as the backbone for different applications either image or video-based. In fact, the authors pretrained the original SWIN transformer on imagenet then they modified the input size and then fine-tuned it on video action recognition datasets. In your case, you can use the original SWIN transformer pretrained on imagenet then fine-tune it on your own dataset without modifying anything about the input size, since it is designed to process images.
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[R] New Study Proposes CW Networks: Greater Expressive Power Than GNNs
The code is available on project GitHub. The paper Video Swin Transformer is on arXiv.
- [R] Video Swin Transformer: SOTA on Video Recognition (84.9% top 1 on Kinetics-400 and 69.6% top 1 on Something-Something V2)
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A note from our sponsor - SaaSHub
www.saashub.com | 28 Apr 2024
Stats
Basic Video-Swin-Transformer repo stats
7
1,309
0.0
about 1 year ago
SwinTransformer/Video-Swin-Transformer is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of Video-Swin-Transformer is Python.
Popular Comparisons
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