XMem
[ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model (by hkchengrex)
hivemind
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world. (by learning-at-home)
| XMem | hivemind | |
|---|---|---|
| 11 | 40 | |
| 1,594 | 1,840 | |
| - | 1.6% | |
| 6.3 | 5.4 | |
| about 2 months ago | about 1 month ago | |
| Python | Python | |
| MIT License | 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.
XMem
Posts with mentions or reviews of XMem.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-11.
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[D] Which open source models can replicate wonder dynamics's drag'n'drop cg characters?
Use Segmentation Model (SAM) combined with Inpainting model (E2FGVI) and Xmem to cut out the live action subject.
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Track-Anything: a flexible and interactive tool for video object tracking and segmentation, based on Segment Anything and XMem.
Nvm just found the occlusion video on https://github.com/hkchengrex/XMem holy shit
- XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
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[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model ( Added because of the Atkinson-Shiffrin Memory Model ) Paper: https://arxiv.org/abs/2207.07115 Github: https://github.com/hkchengrex/XMem
- [D] Most Popular AI Research July 2022 pt. 2 - Ranked Based On GitHub Stars
- Most Popular AI Research July 2022 pt. 2 - Ranked Based On GitHub Stars
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I trained a neural net to watch Super Smash Bros
Yeah MiVOS would speed up your tagging a lot. I also was curious if you saw XMem which just came out. I found that worked really well too.
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University of Illinois Researchers Develop XMem; A Long-Term Video Object Segmentation Architecture Inspired By Atkinson-Shiffrin Memory Model
Continue reading | Check out the paper and github link.
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[R] Unicorn: 🦄 : Towards Grand Unification of Object Tracking(Video Demo)
Have you check XMem?
hivemind
Posts with mentions or reviews of hivemind.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-03-07.
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You can now train a 70B language model at home
https://github.com/learning-at-home/hivemind is also relevant
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Would anyone be interested in contributing to some group projects?
I really hope you'll join me, for the Petals support, at least! A single docker-compose.yml file is all we need, for now. If we are able to find enough people willing to host some smaller models, perhaps we could expand into the Hivemind, and create our own, custom foundation model one day?
- Hive mind:Train deep learning models on thousands of volunteers across the world
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Could a model not be trained by a decentralized network? Like Seti @ home or kinda-sorta like bitcoin. Petals accomplishes this somewhat, but if raw computer power is the only barrier to open-source I'd be happy to try organizing decentalized computing efforts
Decentralized deep learning: https://github.com/learning-at-home/hivemind
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Orca (built on llama13b) looks like the new sheriff in town
https://github.com/learning-at-home/hivemind - same people behind it, was made before petals I think.
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Do you think that AI research will slow down to a halt because of regulation?
not if we rise to meet that challenge. here's a few tools that facilitate AI research in the face of an advanced persistent threat: Hivemind- a distributed Pytorch framework
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LLM@home
yeah, there's Hivemind. and there's research wrt how to chunk out training workload so it can be scaled up. not sure why there's commentary that latency issues would limit this sort of enterprise, the architecture typically isn't designed for liveness. other subfields of distributed training/inference include zero-knowledge machine learning. besides all of that, there's also adversarial computation like SafetyNets and refereed delegation of computation.
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[D] Google "We Have No Moat, And Neither Does OpenAI": Leaked Internal Google Document Claims Open Source AI Will Outcompete Google and OpenAI
We already have the software for it. There are some projects, but the one I'm most familiar with is https://github.com/learning-at-home/hivemind for training and it's sister project https://petals.ml/ for running large models distributed.
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Run 100B+ language models at home, BitTorrent‑style
I'm not entirely how the approach they're using works [0], but I study federated learning and one of the highly-cited survey papers has several chapters (5 and 6 in particular) addressing potential attacks, failure modes, and bias [1].
0: https://github.com/learning-at-home/hivemind
1: https://arxiv.org/abs/1912.04977
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SETI Home Is in Hibernation
The Hivemind project is just that
https://github.com/learning-at-home/hivemind
What are some alternatives?
When comparing XMem and hivemind you can also consider the following projects:
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
replika-research - Replika.ai Research Papers, Posters, Slides & Datasets
flash-attention - Fast and memory-efficient exact attention
GLM-130B - GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
NAFNet - The state-of-the-art image restoration model without nonlinear activation functions.
Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.
deeplab2 - DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks.
alpa - Training and serving large-scale neural networks with auto parallelization.
Cream - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/AutoML]
mesh-transformer-jax - Model parallel transformers in JAX and Haiku
EfficientZero - Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.
HiveMind-core - Join the OVOS collective, utils for OpenVoiceOS mesh networking