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Domain > adaptivetracking.github.io
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Is this malicious?
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DNS Resolutions
Date
IP Address
2017-02-10
151.101.128.133
(
ClassC
)
2024-03-14
185.199.110.153
(
ClassC
)
2025-04-12
185.199.111.153
(
ClassC
)
Port 80
HTTP/1.1 200 OKConnection: keep-aliveContent-Length: 6684Server: GitHub.comContent-Type: text/html; charsetutf-8permissions-policy: interest-cohort()Last-Modified: Wed, 09 Mar 2016 08:28:43 GMTAccess- !DOCTYPE html>html> head> meta charsetutf-8 /> meta http-equivX-UA-Compatible contentchrome1 /> meta namedescription contentAdaptivetracking.github.io : adaptive tracking /> link relstylesheet typetext/css mediascreen hrefstylesheets/stylesheet.css> title>Adaptive tracking/title> /head> body> !-- HEADER --> div idheader_wrap classouter> header classinner> a idforkme_banner hrefhttps://github.com/adaptivetracking/AdaptiveTracking>View on GitHub/a> h1 idproject_title>Adaptive tracking/h1> h2 idproject_tagline>Fusion of tracking techniques to enhance adaptive real-time tracking of arbitrary objects/h2> /header> /div> !-- MAIN CONTENT --> div idmain_content_wrap classouter> section idmain_content classinner> p>This is the homepage of our IHCI 2014 paper em>Fusion of tracking techniques to enhance adaptive real-time tracking of arbitrary objects/em>, which presents an algorithm for tracking arbitrary objects and learning their appearance on-the-fly. The tracking starts with a single annotated frame, where a bounding box around the target is given. The tracking algorithm then computes a new bounding box around the target for each of the following frames and is able to re-detect it after an occlusion. On this website, you can find the code, configurations, and detailled benchmark results that were reported in the paper./p> p>To give an example of what the tracking algorithm should be able to do, we show four frames of sequence F of the a hrefhttp://www.iai.uni-bonn.de/~kleind/tracking/>Bonn Benchmark on Tracking/a>. The blue bounding box is the output of our tracker./p> p styletext-align: center;>img srcimages/frame0.png /> img srcimages/frame130.png /> img srcimages/frame147.png /> img srcimages/frame156.png />/p> p>strong>First image:/strong> Tracking is initialized by the ground truth. strong>Second image:/strong> The algorithm tracks the position of the person. strong>Third image:/strong> There is no bounding b
Port 443
HTTP/1.1 200 OKConnection: keep-aliveContent-Length: 6684Server: GitHub.comContent-Type: text/html; charsetutf-8permissions-policy: interest-cohort()Last-Modified: Wed, 09 Mar 2016 08:28:43 GMTAccess- !DOCTYPE html>html> head> meta charsetutf-8 /> meta http-equivX-UA-Compatible contentchrome1 /> meta namedescription contentAdaptivetracking.github.io : adaptive tracking /> link relstylesheet typetext/css mediascreen hrefstylesheets/stylesheet.css> title>Adaptive tracking/title> /head> body> !-- HEADER --> div idheader_wrap classouter> header classinner> a idforkme_banner hrefhttps://github.com/adaptivetracking/AdaptiveTracking>View on GitHub/a> h1 idproject_title>Adaptive tracking/h1> h2 idproject_tagline>Fusion of tracking techniques to enhance adaptive real-time tracking of arbitrary objects/h2> /header> /div> !-- MAIN CONTENT --> div idmain_content_wrap classouter> section idmain_content classinner> p>This is the homepage of our IHCI 2014 paper em>Fusion of tracking techniques to enhance adaptive real-time tracking of arbitrary objects/em>, which presents an algorithm for tracking arbitrary objects and learning their appearance on-the-fly. The tracking starts with a single annotated frame, where a bounding box around the target is given. The tracking algorithm then computes a new bounding box around the target for each of the following frames and is able to re-detect it after an occlusion. On this website, you can find the code, configurations, and detailled benchmark results that were reported in the paper./p> p>To give an example of what the tracking algorithm should be able to do, we show four frames of sequence F of the a hrefhttp://www.iai.uni-bonn.de/~kleind/tracking/>Bonn Benchmark on Tracking/a>. The blue bounding box is the output of our tracker./p> p styletext-align: center;>img srcimages/frame0.png /> img srcimages/frame130.png /> img srcimages/frame147.png /> img srcimages/frame156.png />/p> p>strong>First image:/strong> Tracking is initialized by the ground truth. strong>Second image:/strong> The algorithm tracks the position of the person. strong>Third image:/strong> There is no bounding b
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