source: image by author. The FixEfficientNet has been presented first with the corresponding paper on the 20th April 2020 from the Facebook AI Research Team . It is currently the state-of-the-art and has the best results on the ImageNet Dataset with 480M params, a top-1 accuracy of 88.5%, and top-5 accuracy of 98,7%.
[Code (Github)] Abstract The ability to generate novel, diverse, and realistic 3D shapes along with associated part semantics and structure is central to many applications requiring high-quality 3D assets or large volumes of realistic training data.
Isaac Distributed Workspace on github provides example(s) for partners (such as sensors, algorithms, used by Isaac SDK) to create such compatible workspaces and contribute directly to Isaac SDK. The GitHub repository hosted by NVIDIA Isaac Robotics team, provides a mechanism to track dependencies between packages, and separate out dependency ...
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近期必读的六篇计算机视觉顶会ECCV 2020【目标检测】相关论文 - 专知
We evaluate the approach qualitatively on several real-world datasets (ScanNet, Matterport3D, KITTI), quantitatively on 3D-EPN shape completion benchmark dataset, and demonstrate realistic completions under varying levels of incompleteness. Keywords: point cloud completion, generative adversarial network, real scans