Mega.Pytorch

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mega.pytorch is an open-source implementation of Memory Enhanced Global-Local Aggregation for Video Object Detection. It provides a PyTorch implementation of the MEGA architecture for researchers.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is mega.pytorch?

mega.pytorch offers an official PyTorch implementation of the "Memory Enhanced Global-Local Aggregation for Video Object Detection" (MEGA) approach, which was accepted by CVPR 2020. This repository is built upon maskrcnn_benchmark and includes training scripts to replicate results on ImageNet VID. Beyond MEGA, it also implements other video object detection algorithms like FGFA and RDN, welcoming contributions for new methods. The project aims to support further research in video object detection, providing pretrained models and detailed instructions for installation, data preparation, inference, and training.

Best used for

Ideal for AI researchers and computer vision engineers who need to implement and benchmark state-of-the-art video object detection models, reproduce published research results, and develop new algorithms. Especially valuable for those working with PyTorch and the ImageNet VID dataset.

Common actions

implement video object detection

benchmark computer vision models

reproduce research results

develop new algorithms

"AI Agents"face swappinggithub copilotopen-sourcedeepfakeworkflowslow-code/no-codecollaborationautomated workflow

Capabilities

Key features

Memory Enhanced Global-Local Aggregation
Video object detection
PyTorch implementation
ImageNet VID dataset support
Pretrained models available
Motion-IoU AP evaluation
FGFA and RDN algorithms

Target Audience

professordeveloperresearcher

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What is the primary research paper implemented by mega.pytorch?

mega.pytorch is an official implementation of the paper "Memory Enhanced Global-Local Aggregation for Video Object Detection," which was accepted by CVPR 2020. It provides the PyTorch code and resources to reproduce the results presented in this research.

Does mega.pytorch support other video object detection algorithms besides MEGA?

Yes, in addition to the MEGA architecture, this repository also includes implementations of several other video object detection algorithms such as FGFA and RDN. This allows for comparative studies and broader research within the field.

What datasets are supported for training and evaluation with mega.pytorch?

The project is designed to work with the ILSVRC2015 DET and ILSVRC2015 VID datasets. Users are instructed to download these datasets and symlink them to the project's datasets directory for proper setup and usage.

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Research & Education › Academic Research

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