Pinned Repositories
CenterNet
Object detection, 3D detection, and pose estimation using center point detection:
RFBNet
Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018
SSD-Tensorflow
Single Shot MultiBox Detector in TensorFlow
TensorRT
TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.
TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
lsdNorman's Repositories
lsdNorman/CenterNet
Object detection, 3D detection, and pose estimation using center point detection:
lsdNorman/RFBNet
Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018
lsdNorman/SSD-Tensorflow
Single Shot MultiBox Detector in TensorFlow
lsdNorman/TensorRT
TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.
lsdNorman/TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.