zhahu315's Stars
ctgk/PRML
PRML algorithms implemented in Python
dk-liang/Awesome-Visual-Transformer
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)
lucidrains/vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
JunMa11/SegLossOdyssey
A collection of loss functions for medical image segmentation
MenghaoGuo/Awesome-Vision-Attentions
Summary of related papers on visual attention. Related code will be released based on Jittor gradually.
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Tencent/TurboTransformers
a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.
gmalivenko/onnx-opcounter
Count number of parameters / MACs / FLOPS for ONNX models.
xmu-xiaoma666/External-Attention-pytorch
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
rafellerc/Pytorch-SiamFC
Pytorch implementation of "Fully-Convolutional Siamese Networks for Object Tracking"
Anduin2017/HowToCook
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
yhenon/pytorch-retinanet
Pytorch implementation of RetinaNet object detection.
yatengLG/Retinanet-Pytorch
Retinanet目标检测算法(简单,明了,易用,全中文注释,单机多卡训练,视频检测)(based on pytorch,Simple, Clear, Mutil GPU)
GATECH-EIC/DepthShrinker
[ICML 2022] "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks", by Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin
Tianfang-Zhang/awesome-infrared-small-targets
List of awesome infrared small targets detection methods!
666DZY666/micronet
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
Mikoto10032/DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
NVIDIA/DeepLearningExamples
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Jamie725/Multimodal-Object-Detection-via-Probabilistic-Ensembling
qfgaohao/pytorch-ssd
MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv.
tensorflow/models
Models and examples built with TensorFlow
SensorsINI/v2e
V2E: From video frames to DVS events
jwyang/faster-rcnn.pytorch
A faster pytorch implementation of faster r-cnn
STVIR/pysot
SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
midasklr/SSD.Pytorch
Pytorch implementation of SSD512
mli/paper-reading
深度学习经典、新论文逐段精读
TheAlgorithms/Python
All Algorithms implemented in Python
ziqiangt/vim-init
轻量级 Vim 配置框架,全中文注释
nvdla/hw
RTL, Cmodel, and testbench for NVDLA