# foolwood/SiamMask

[CVPR19/TPAMI23] SiamMask: A Framework for Fast Online Object Tracking and Segmentation

Repository: https://github.com/foolwood/SiamMask
Canonical: https://ross.abutalabs.com/products/siammask
Homepage: http://www.robots.ox.ac.uk/~qwang/SiamMask
Language: Python
License: MIT
License Family: permissive
Topics: visual-tracking, video-object-segmentation, read-time, pytorch, deep-learning, cvpr2019, computer-vision, object-tracking
Last push: 2025-02-14T03:39:33+00:00

## Health v2 (maintenance only)
Score: 35/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 6, release rhythm 35, longevity 100
- inputs: {"age_days": 2739, "days_push": 565, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3547, forks 804 (observed 2026-08-28T04:08:09.436407+00:00)

## What it is
Official PyTorch implementation of SiamMask, a deep learning framework for fast online visual object tracking and video object segmentation. It unifies tracking and segmentation in a single network, published at CVPR 2019 and extended in TPAMI 2023.

## Use cases
- track objects in video in real time
- segment a target object across video frames
- reproduce CVPR 2019 object tracking results
- train a siamese tracking model from scratch
- benchmark on VOT2018 visual tracking
- generate binary masks for moving objects in video

## When to choose
- you need a proven, published model for joint object tracking and segmentation
- you want official training and inference code with reproducible paper results
- you need real-time tracking performance on GPU hardware

## When to avoid
- you need a maintained production library with modern PyTorch support - the code targets old PyTorch 0.4.1 and Python 3.6
- you need multi-object tracking or detection, since SiamMask tracks a single initialized target
- you want the latest state-of-the-art trackers rather than a 2019 research baseline

## Facets
- artifact type: library
- maturity: maintenance
- function: computer-vision, image-processing, deep-learning, machine-learning
- domain: computer-vision, image-processing, deep-learning, machine-learning
- platform: python
- tags: object-tracking, video-object-segmentation, pytorch, siamese-network, cvpr2019, research-code, video, linux, gpu

## Member repositories
- foolwood/SiamMask (main) score 35

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:09.436407+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:34:23.468002+00:00, confidence not recorded.
  - readme: https://github.com/foolwood/SiamMask (fetched 2026-08-28T04:08:09.436407+00:00, sha b578bc6ab565)
- Data as of 2026-08-30T08:39:29.467469+00:00.