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This is the official repo for the CVPR 2021 IMW paper: "Perceptual Loss for Robust Unsupervised Homography Estimation"
Pytorch implementation of Unsupervised Deep Homography.
image registration related books, papers, videos, and toolboxes
This is the open source implementation of the CVPR2022 paper "Iterative Deep Homography Estimation"
Official implementation of CATs
收集 CVPR 最新的成果，包括论文、代码和demo视频等，欢迎大家推荐！Collect the latest CVPR (Conference on Computer Vision and Pattern Recognition) results, including papers, code, and demo videos, etc., and welcome recommendati…
A Collection of Papers and Codes in CVPR2023/2022 about low level vision
Implementation of PFLD For 68 Facial Landmarks By Pytorch
Facial Landmark Detection based on PyTorch
Fast and accurate face landmark detection library using PyTorch; Support 68-point semi-frontal and 39-point profile landmark detection; Support both coordinate-based and heatmap-based inference; Up…
based on yolo-high-level project (detect\pose\classify\segment\):include yolov5\yolov7\yolov8\ core ,improvement research ,SwintransformV2 and Attention Series. training skills, business customizat…
YOLOv5 in TF2 > TFLite > ONNX > TensorRT
A paper list of object detection using deep learning.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
First project for CVND: facial keypoint detection.
利用SSD目标检测算法判断是否闭眼或者张开嘴和吸烟打电话等手势行为，通过PERCLOS准则判断是否疲劳等等，功能涵盖7类情绪识别，眨眼判断，哈欠判断，吸烟，打电话等，达到危险驾驶检测的功能
kaggle中的【State Farm Distracted Driver Detection】比赛的实现
Solves a kaggle problem of State Farm Distracted Driver Detection
基于深度学习的驾驶员状态检测，不仅仅可以识别出疲劳驾驶，还能够识别出各种各样的状态
This is a project based on a research paper to detect fatigue levels of a person through a photograph.
本科毕设内容：基于卷积神经网络的疲劳驾驶检测。
AMC-IoT: Automatic Modulation Classification Using Efficient Convolutional Neural Networks for Low Power IoT Devices
MCNet: An Efficient CNN Architecture for Robust Automatic Modulation Classification
Automatic Modulation Classification implemented on different deep learning frameworks
Machine Learning for Wireless communications course project on Sequential Convolutional Recurrent Neural Networks for fast automatic modulation classification.