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Deep Learning Inference benchmark. Supports OpenVINO™ toolkit, TensorFlow, TensorFlow Lite, ONNX Runtime, OpenCV DNN, MXNet, PyTorch, Apache TVM, ncnn, PaddlePaddle, etc.
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Pytorch implementation of the ECCV 2020 paper: AtlantaNet: Inferring the 3D Indoor Layout from a Single 360 Image beyond the Manhattan World Assumption
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A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
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This is PyTorch implementation of our paper "LGT-Net: Indoor Panoramic Room Layout Estimation with Geometry-Aware Transformer Network".(CVPR'22)
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CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering" official PyTorch implementation.
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Pre-trained Deep Learning models and demos (high quality and extremely fast)
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#CV-SUMMER-CAMP-2022 Репозиторий материалов Летней школы ННГУ им. Н.И. Лобачевского по компьютерному зрению
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Pre-trained Deep Learning models and samples (high quality and extremely fast)
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