From 9ff2e12955bc35625fc5ec7f4bfe6cadee91b214 Mon Sep 17 00:00:00 2001 From: menelaos kanakis Date: Mon, 21 Nov 2022 14:59:11 +0100 Subject: [PATCH] Update README for ETTrack --- README.md | 20 ++++++++++++++++---- pytracking/.figs/ETTrack_overview.png | Bin 0 -> 2213177 bytes 2 files changed, 16 insertions(+), 4 deletions(-) create mode 100644 pytracking/.figs/ETTrack_overview.png diff --git a/README.md b/README.md index 2f882f9..d6c086e 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,9 @@ # PyTracking A general python framework for visual object tracking and video object segmentation, based on **PyTorch**. +### :fire: One tracking paper accepted at WACV 2023! 👇 +* [Efficient Visual Tracking with Exemplar Transformers](https://arxiv.org/abs/2112.09686) | **Code available!** + ### :fire: One tracking paper accepted at ECCV 2022! 👇 * [Robust Visual Tracking by Segmentation](https://arxiv.org/abs/2203.11191) | **Code available!** @@ -11,10 +14,6 @@ A general python framework for visual object tracking and video object segmentat ### One tracking paper accepted at CVPR 2022! * [Transforming Model Prediction for Tracking](https://arxiv.org/abs/2203.11192) | **Code available!** -### Two tracking/VOS papers accepted at ICCV 2021! -* [Learning Target Candidate Association to Keep Track of What Not to Track](https://arxiv.org/abs/2103.16556) | **Code available!** -* [Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos](https://arxiv.org/abs/2101.02196) | Code coming here soon... - ## Highlights @@ -157,6 +156,19 @@ An unofficial implementation of the **ECO** tracker. It is implemented based on Please refer to the [official implementation of ECO](https://github.com/martin-danelljan/ECO) if you are looking to reproduce the results in the ECO paper or download the raw results. +## Associated trackers +We list associated trackers that can be found in external repositories. + +### E.T.Track (WACV 2023) + +**[[Paper]](https://arxiv.org/abs/2112.09686) [[Code]](https://github.com/pblatter/ettrack)** + +Official implementation of **E.T.Track**. E.T.Track utilized our proposed Exemplar Transformer, a transformer module +utilizing a single instance level attention layer for realtime visual object tracking. E.T.Track is up to 8x faster than +other transformer-based models, and consistently outperforms competing lightweight trackers that can operate in realtime +on standard CPUs. + +![ETTrack_teaser_figure](pytracking/.figs/ETTrack_overview.png) ## Installation diff --git a/pytracking/.figs/ETTrack_overview.png b/pytracking/.figs/ETTrack_overview.png new file mode 100644 index 0000000000000000000000000000000000000000..495cbde32d24e37787dcfd1071b1bfd473cd4388 GIT binary patch literal 2213177 zcmYhjN3QK!w;px{7=j@{9S{V#^aFC?{a_A7l8bRMlZ&bH%$##(*%fz2O;A}S^}}^H zz?0`b0Xk;~E{4e&M*PM%_y1$+;(z=P|LH&c_19njQI~@2ZF@Y z^v|r0%O&pDe-8NuPJ!$FnAJs{XMf*=KnU_LF#InF?84|jPzFW74;=p|LXy$n_s3;E z{9A+gKOxY-f6?N!9=36<{(-XKvpj5h2Y!Ro;HTk$9|8D=p?`((eAT-k#{v6P`O60XdD2E|)$(mY!4!$c=-Ki*{5P#mmkkfTx zaA|yW^pPm@YRuxIjR~s##hg*g@;_?<2QroGXi_s>&!?v{nCnh}`4EWTMC6OfeDFRr znJ;7#yan%{>YWhE%sxSGVW4%;U6BAotK{4_}4~aZdDD`-&4NgbT2MHckbVAbS@P zQErETun@K@Qbji3RS637euSbMIJ7Pl__+V9=!M@}@2=(`UDbOR1-@TF`FTIW1(VL6 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