Jack-ouc

Jack-ouc

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Jack-ouc's repositories

DenseNAS

Densely Connected Search Space for More Flexible Neural Architecture Search (CVPR2020)

License:Apache-2.0Stargazers:0Issues:0Issues:0

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

License:BSD-3-ClauseStargazers:0Issues:0Issues:0

detectron2

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

License:Apache-2.0Stargazers:0Issues:0Issues:0

mmdetection

Open MMLab Detection Toolbox and Benchmark

License:Apache-2.0Stargazers:0Issues:0Issues:0

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more

License:Apache-2.0Stargazers:0Issues:0Issues:0

AlphaPose

Real-Time and Accurate Multi-Person Pose Estimation&Tracking System

License:NOASSERTIONStargazers:0Issues:0Issues:0

EfficientDet.Pytorch

Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch

License:MITStargazers:1Issues:0Issues:0

darknet

Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection (Tensor Cores are used)

License:NOASSERTIONStargazers:0Issues:0Issues:0

PC-DARTS

PC-DARTS:Partial Channel Connections for Memory-Efficient Differentiable Architecture Search

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Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

License:Apache-2.0Stargazers:0Issues:0Issues:0

darts

Differentiable architecture search for convolutional and recurrent networks

License:Apache-2.0Stargazers:0Issues:0Issues:0

ProxylessNAS

[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware.

License:Apache-2.0Stargazers:0Issues:0Issues:0
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pdarts

Codes for our paper "Progressive Differentiable Architecture Search:Bridging the Depth Gap between Search and Evaluation"

License:NOASSERTIONStargazers:0Issues:0Issues:0

DARTS-1

Differentiable architecture search for convolutional and recurrent networks

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