mmhuman3d
mmselfsup
mmhuman3d | mmselfsup | |
---|---|---|
5 | 5 | |
1,124 | 3,084 | |
1.9% | 0.7% | |
2.5 | 5.3 | |
7 days ago | 10 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
mmhuman3d
-
MMDeploy: Deploy All the Algorithms of OpenMMLab
MMHuman3D: OpenMMLab 3D human parametric model toolbox and benchmark.
-
What software can convert camera footage to a skeleton animation?
You might want to check out https://github.com/open-mmlab/mmhuman3d and https://github.com/google/mediapipe
-
MMHuman3D
We have released an @OpenMMLab human pose and shape estimation toolbox "MMHuman3D":
https://github.com/open-mmlab/mmhuman3d
- Popular methods with a modular framework
mmselfsup
-
MMDeploy: Deploy All the Algorithms of OpenMMLab
MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
-
Does anyone know how a loss curve like this can happen? Details in comments
For some reason, the loss goes up shaply right at the start and slowly goes back down. I am self-supervised pretraining an image modeling with DenseCL using mmselfsup (https://github.com/open-mmlab/mmselfsup). This shape happened on the Coco-2017 dataset and my custom dataset. As you can see, it happens consistently for different runs. How could the loss increase so sharply and is it indicative of an issue with the training? The loss peaks before the first epoch is finished. Unfortunately, the library does not support validation.
- Defect Detection using RPI
- [D] State-of-the-Art for Self-Supervised (Pre-)Training of CNN architectures (e.g. ResNet)?
- Rebirth! OpenSelfSup is upgraded to MMSelfSup
What are some alternatives?
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
mmfewshot - OpenMMLab FewShot Learning Toolbox and Benchmark
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
mmflow - OpenMMLab optical flow toolbox and benchmark
calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
mim - MIM Installs OpenMMLab Packages
mmagic - OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.
mmcv - OpenMMLab Computer Vision Foundation
barlowtwins - Implementation of Barlow Twins paper
openvino - OpenVINOâ„¢ is an open-source toolkit for optimizing and deploying AI inference
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]