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annotated_deep_learning_paper_implementations icon annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

centertrack icon centertrack

Simultaneous object detection and tracking using center points.

co-tracker icon co-tracker

CoTracker is a model for tracking any point (pixel) on a video.

conv_arithmetic icon conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

csk icon csk

Circulant Structure of Tracking-by-detection with Kernels

dcfnet_pytorch icon dcfnet_pytorch

DCFNet: Discriminant Correlation Filters Network for Visual Tracking

dcnv2 icon dcnv2

Deformable Convolutional Networks v2 with Pytorch

deep_sort icon deep_sort

Simple Online Realtime Tracking with a Deep Association Metric

deeplearning icon deeplearning

A deep learning code base, mainly for paper replication, in the areas of image recognition, object detection, image segmentation, self-supervision, etc. Each project can be run independently, and there are corresponding articles to explain.

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

ema-attention-module icon ema-attention-module

Implementation Code for the ICCASSP 2023 paper " Efficient Multi-Scale Attention Module with Cross-Spatial Learning" and is available at: https://arxiv.org/abs/2305.13563v2

istdu-net icon istdu-net

code of article ISTDU-Net:Infrared Small-Target Detection U-Net

jetson-inference icon jetson-inference

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

kalman-cpp icon kalman-cpp

Basic Kalman filter implementation in C++ using Eigen

kalman-tracker icon kalman-tracker

An algorithm for object tracking based on Kalman Filter is implemented using OpenCV C++ library. Two modes of operation are coded, a Constant Velocity Model, and an Acceleration Model.

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