UniTrack
Unicorn
| UniTrack | Unicorn | |
|---|---|---|
| 1 | 7 | |
| 335 | 942 | |
| - | - | |
| 1.8 | 0.0 | |
| about 2 years ago | over 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
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.
UniTrack
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Multi Object Tracking from moving camera
Great suggestion! I’ll add the github link.
Unicorn
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need help with object detection and object tracking using yolov4
Also check out Unicorn - https://github.com/MasterBin-IIAU/Unicorn
- [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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Researchers from Bytedance and Dalian University Propose 🦄 ‘Unicorn’: a Unified Computer Vision Approach to Address Four Tracking Tasks Using a Single Model with the Same Model Parameters
Continue reading | Checkout the paper and github link
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[R] Unicorn: 🦄 : Towards Grand Unification of Object Tracking(Video Demo)
Brief Overview We present a unified method, termed Unicorn, that can simultaneously solve four tracking problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters. For the first time, we accomplished the great unification of the tracking network architecture and learning paradigm. Unicorn performs on-par or better than its task-specific counterparts in 8 tracking datasets, including LaSOT, TrackingNet, MOT17, BDD100K, DAVIS16-17, MOTS20, and BDD100K MOTS. Our work is accepted to ECCV 2022 as an oral presentation ! Paper: https://arxiv.org/abs/2207.07078 Code: https://github.com/MasterBin-IIAU/Unicorn
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[R] Unicorn: 🦄 : Towards Grand Unification of Object Tracking
Code for https://arxiv.org/abs/2207.07078 found: https://github.com/MasterBin-IIAU/Unicorn
What are some alternatives?
mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
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.
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
UNINEXT - [CVPR'23] Universal Instance Perception as Object Discovery and Retrieval
theseus - A library for differentiable nonlinear optimization
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
NUWA - A unified 3D Transformer Pipeline for visual synthesis
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
Cream - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/AutoML]
multiface - Hosts the Multiface dataset, which is a multi-view dataset of multiple identities performing a sequence of facial expressions.