This is the mmdetection implementation of our CVPR2021 paper:
Zhenyu Wang, Yali Li, Ye Guo, Lu Fang, Shengjin Wang. Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection. ArXiv.
This code is based on mmdetection v2.18. Please install the code according to the mmdetection step first.
kenyan-Siri Build an Artificial Assistant Full tutorial (video) To watch the tutorial, click on the image below Installation For windows users (run th
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Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning (c) Tianyu Han and Daniel Truhn, RWTH Aachen University, 20
Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image
Grow Function: A 3D Stacked Bifurcating Double Deep Cellular Automata which differentiates using a Genetic Algorithm... TLDR;High Def Trees that you can mint as NFTs on Solana
RNN-for-Predicting-Street-Vitality Code and dataset for Predicting the Vitality of Stores along the Street based on Business Type Sequence via Recurre
Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report
2048-expectimax Simulating an AI playing 2048 using the Expectimax algorithm The base game engine uses code from here. The AI player is modeled as a m
Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process, a complete algorithm library is esta
DFM: A Performance Baseline for Deep Feature Matching Python (Pytorch) and Matlab (MatConvNet) implementations of our paper DFM: A Performance Baselin
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh
Kroomsa A search engine for the curious. It is a search algorithm designed to en
Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio
🧠kendrite A framework for attentive explainable deep learning on tabular data 💨 Quick start kedro run 🧱 Built upon Technology Description Links ke
RoMA: Robust Model Adaptation for Offline Model-based Optimization Implementation of RoMA: Robust Model Adaptation for Offline Model-based Optimizatio
pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Learning multiple gaits of quadruped robot using hierarchical reinforcement learning We propose a method to learn multiple gaits of quadruped robot us
SlowFast A PyTorch implementation of SlowFast based on ICCV 2019 paper SlowFast Networks for Video Recognition. Requirements Anaconda PyTorch conda in
TL;DR Ignite is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Click on the image to
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