XMem
EfficientZero
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| XMem | EfficientZero | |
|---|---|---|
| 10 | 9 | |
| 1,171 | 714 | |
| - | - | |
| 8.2 | 2.6 | |
| 9 days ago | 10 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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
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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
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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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[R] Unicorn: 🦄 : Towards Grand Unification of Object Tracking(Video Demo)
Have you check XMem?
EfficientZero
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[D] GPT-3T: Can we train language models to think further ahead?
Here's an algorithm that is more sample efficient : https://github.com/YeWR/EfficientZero
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MuZero learns to play Teamfight Tactics
Use multiprocessing to have more GPU workers could help. My code based on EfficientZero https://github.com/YeWR/EfficientZero is utilizing CPUs and GPUs to 90%. It uses Ray for multiprocessing and splits Reanalyze into CPU and GPU workers to maximize resource utilization. By the way, it's not converging to optimal policy well: it gets stuck at 50% optimal episode return at with a small amount of training. Have you had this issue before?
- Anyone found any working replication repo for MuZero?
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[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
Mastering Atari Games with Limited Data – EfficientZero ( Human sample -efficiency! ) Paper: https://arxiv.org/abs/2111.00210 Lesswrong article about the paper: https://www.lesswrong.com/posts/mRwJce3npmzbKfxws/efficientzero-how-it-works Github: https://github.com/YeWR/EfficientZero
What are some alternatives?
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
flash-attention - Fast and memory-efficient exact attention
flash-attention-jax - Implementation of Flash Attention in Jax
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.
multiface - Hosts the Multiface dataset, which is a multi-view dataset of multiple identities performing a sequence of facial expressions.
NUWA - A unified 3D Transformer Pipeline for visual synthesis
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
NAFNet - The state-of-the-art image restoration model without nonlinear activation functions.
msn - Masked Siamese Networks for Label-Efficient Learning (https://arxiv.org/abs/2204.07141)
Cream - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/AutoML]