UniTrack
UNINEXT
| UniTrack | UNINEXT | |
|---|---|---|
| 1 | 2 | |
| 335 | 1,447 | |
| - | - | |
| 1.8 | 5.5 | |
| about 2 years ago | 10 months ago | |
| Python | Python | |
| MIT License | MIT License |
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UniTrack
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Multi Object Tracking from moving camera
Great suggestion! I’ll add the github link.
UNINEXT
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[R] Universal Instance Perception as Object Discovery and Retrieval (Video Demo)
Hi, we have uploaded the complete paper (https://github.com/MasterBin-IIAU/UNINEXT/blob/master/assets/UNINEXT_Paper.pdf) to our repo. You can find more details in the paper :) About the first question, the input videos are NOT segmented aforehand and all target masks are predicted by our UNINEXT model. For SOT and VOS, we use target annotations (box or mask) from the first frame as the prompts. This helps UNINEXT to segment corresponding targets in the following frames.
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.
VolleyVision - Applying Deep Learning Approaches to Volleyball Data
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
ailia-models - The collection of pre-trained, state-of-the-art AI models for ailia SDK
py-motmetrics - :bar_chart: Benchmark multiple object trackers (MOT) in Python
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
TagMaps - Spatio-Temporal Tag and Photo Location Clustering for generating Tag Maps
unimatch - [TPAMI'23] Unifying Flow, Stereo and Depth Estimation
VNext - Next-generation Video instance recognition framework on top of Detectron2 which supports InstMove (CVPR 2023), SeqFormer(ECCV Oral), and IDOL(ECCV Oral))