UNINEXT
VolleyVision
| UNINEXT | VolleyVision | |
|---|---|---|
| 2 | 2 | |
| 1,443 | 141 | |
| - | - | |
| 5.5 | 8.7 | |
| 10 months ago | 29 days ago | |
| Python | Python | |
| MIT License | GNU Affero General Public License v3.0 |
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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.
VolleyVision
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Open-Source Hawkeye for Volleyball
Yo can find the code and datasets on GitHub - VolleyVision.
Check out the code on GitHbu - VolleVision
What are some alternatives?
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
multi-object-tracker - Multi-object trackers in Python
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
gluon-cv - Gluon CV Toolkit
TagMaps - Spatio-Temporal Tag and Photo Location Clustering for generating Tag Maps
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
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))
UniTrack - [NeurIPS'21] Unified tracking framework with a single appearance model. It supports Single Object Tracking (SOT), Video Object Segmentation (VOS), Multi-Object Tracking (MOT), Multi-Object Tracking and Segmentation (MOTS), Pose Tracking, Video Instance Segmentation (VIS), and class-agnostic MOT (e.g. TAO dataset).