Allez Shi's Projects
Code for CVPR2021 paper "Learning Salient Boundary Feature for Anchor-free Temporal Action Localization"
Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
An open autonomous driving platform
[CVPR2020] "Detecting Attended Visual Targets in Video"
Add bisenetv2. My implementation of BiSeNet
Implementation for Bottom-Up Temporal Action Localization with Mutual Regularization (ECCV2020)
A pytorch-version implementation codes of paper: "BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation", which is accepted in AAAI 2021.
Simultaneous object detection and tracking using center points.
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Deformable Convolutional Networks v2 with Pytorch
The official implementation of "Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes"
深度学习与PyTorch入门实战视频教程 配套源代码和PPT
Extracting optical flow and frames
A simple baseline for one-shot multi-object tracking
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Automatically generate summary GitHub statistics images for your profile using Actions, no server required
类似按键精灵的鼠标键盘录制和自动化操作 模拟点击和键入 | automate mouse clicks and keyboard input
🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images
PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
Pre-trained and Reproduced Deep Learning Models (『飞桨』官方模型库,包含多种学术前沿和工业场景验证的深度学习模型)
Code for the paper "Multi-shot Temporal Event Localization: a Benchmark", CVPR 2021
Visualizer for neural network, deep learning, and machine learning models
Colar: Effective and Efficient Online Action Detection by Consulting Exemplars, CVPR 2022.
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.
Annotate quickly images.