zhouxinqing

zhouxinqing's Stars

• wmathor/nlp-tutorial

  Natural Language Processing Tutorial for Deep Learning Researchers

  Language:Jupyter Notebook1k354

• Miraclelucy/dive_into_deep_learning

  ✔️李沐 【动手学深度学习】课程学习笔记：使用pycharm编程，基于pytorch框架实现。

  Language:Python2.4k451

• ZhangGongjie/IMFA

  Language:Python43

• deepseek-ai/DeepSeek-V2

  DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

  3.4k134

• ahmedtarek97/dreyeve

  Language:Python31

• TomMao23/multiyolov5

  joint detection and semantic segmentation, based on ultralytics/yolov5,

  Language:Python658147

• soniabaee/MEDIRL-EyeCar

  Language:Jupyter Notebook4613

• tensorflow/models

  Models and examples built with TensorFlow

  Language:Python77k45.8k

• VDIGPKU/HENet

  [ECCV 2024] HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras

  413

• LinShan-Bin/OccNeRF

  Code of "OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments".

  Language:Python30017

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python53.9k5.6k

• lutzroeder/netron

  Visualizer for neural network, deep learning and machine learning models

  Language:JavaScript27.5k2.7k

• HarisIqbal88/PlotNeuralNet

  Latex code for making neural networks diagrams

  Language:TeX21.8k2.8k

• WongKinYiu/yolov9

  Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

  Language:Python8.8k1.4k

• JiayuanWang-JW/YOLOv8-multi-task

  Language:Python23039

• IEIAuto/AutoDRRT

  Language:C++167

• CVHub520/X-AnyLabeling

  Effortless data labeling with AI support from Segment Anything and other awesome models.

  Language:Python3.7k417

• ndrplz/dreyeve

  [TPAMI 2018] Predicting the Driver’s Focus of Attention: the DR(eye)VE Project. A deep neural network learnt to reproduce the human driver focus of attention (FoA) in a variety of real-world driving scenarios.

  Language:C9733

• JWFangit/LOTVS-DADA

  Driver Attention Prediction in Accidental Scenarios

  Language:Python8811

• pascalxia/driver_attention_prediction

  Language:Python3518

• CAIC-AD/YOLOPv2

  YOLOPv2: Better, Faster, Stronger for Panoptic driving Perception

  Language:Python54167

• ultralytics/JSON2YOLO

  Convert JSON annotations into YOLO format.

  Language:Python807228

• hustvl/YOLOP

  You Only Look Once for Panopitic Driving Perception.（MIR2022）

  Language:Python1.9k411

• jiaoZ7688/YOLOPX

  Language:Python201

• WZMIAOMIAO/deep-learning-for-image-processing

  deep learning for image processing including classification and object-detection etc.

  Language:Python22.4k7.9k

• z1069614715/objectdetection_script

  一些关于目标检测的脚本的改进思路代码，详细请看readme.md

  Language:Python5.1k461

• ultralytics/ultralytics

  NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

  Language:Python28.4k5.6k