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Academic Torrents
Aug 11, 2020 M{\"u}ller, Matthias; Bibi, Adel; Giancola, Silvio; Al-Subaihi, Salman; Ghanem, Bernard
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Source: http://academictorrents.com/details/1faf1b53cc0099d2206f02be42b5688952c3c6b3
Academic Torrents
Feb 11, 2019 BraTS
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Source: http://academictorrents.com/details/a9e2741587d42ef6139aa474a95858a17952b3a5
Academic Torrents
Feb 11, 2019 BraTS
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Source: http://academictorrents.com/details/a5912da845c7d7bec9bd0880c17ddda789ba35d5
Academic Torrents
Feb 11, 2019 Antonini, Amado; Guerra, Winter; Murali, Varun; Sayre-McCord, Thomas; Karaman, Sertac
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The Blackbird unmanned aerial vehicle (UAV) dataset is a large-scale indoor dataset collected using a custom-built quadrotor platform for use in evaluation of agile perception. The dataset contains over 10 hours of flight data from 168 flights over 17 flight trajectories and 5 environments at velocities up to 8.0 m/s. Each flight includes sensor data from 120 Hz stereo and downward-facing photorealistic virtual cameras, 100 Hz IMU, 190 Hz motor speed sensors, and 360 Hz millimeter-accurate...
Topics: UAV, aggressive, dataset, drone racing, VIO, SLAM, perception
Source: http://academictorrents.com/details/eb542a231dbeb2125e4ec88ddd18841a867c2656
Academic Torrents
Feb 11, 2019 Liu, Qi; Allamanis, Miltiadis; Brockschmidt, Marc; Gaunt, Alex; er L.
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ZINC is a free database of commercially-available compounds for virtual screening. ZINC contains over 230 million purchasable compounds in ready-to-dock, 3D formats. ZINC also contains over 750 million purchasable compounds you can search for analogs in under a minute. Sterling and Irwin, J. Chem. Inf. Model, 2015 http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00559 This particular dataset comes from the paper Constrained Graph Variational Autoencoders for Molecule Design, Qi Liu, Miltiadis...
Topics: zinc, graph generation, molecule generation
Source: http://academictorrents.com/details/4776b264ca3c4ed05530124b6319ce0d45aff626
Academic Torrents
Feb 11, 2019 Eric Hofesmann; Madan Ravi Ganesh; Jason J. Corso
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There are many hurdles that prevent the replication of existing work which hinders the development of new activity classification models. These hurdles include switching between multiple deep learning libraries and the development of boilerplate experimental pipelines. We present M-PACT to overcome existing issues by removing the need to develop boilerplate code which allows users to quickly prototype action classification models while leveraging existing state-of-the-art (SOTA) models...
Topics: actvity recognition, weights, c3d, i3d, tsn, resnet, lstm
Source: http://academictorrents.com/details/dcea7fa53925b31215bd8437d2f0805253d6b00f