Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

Related tags

Deep Learningobject-detectionsemi-supervisedcvpr2021
Overview

Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

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.

Owner
GitHub Repository
Tensorflow Implementation of ECCV'18 paper: Multimodal Human Motion Synthesis

MT-VAE for Multimodal Human Motion Synthesis This is the code for ECCV 2018 paper MT-VAE: Learning Motion Transformations to Generate Multimodal Human

Xinchen Yan 36 Oct 02, 2022
Pyramid Pooling Transformer for Scene Understanding

Pyramid Pooling Transformer for Scene Understanding Requirements: torch 1.6+ torchvision 0.7.0 timm==0.3.2 Validated on torch 1.6.0, torchvision 0.7.0

Yu-Huan Wu 119 Dec 29, 2022
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation.

ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too

e-Lab 344 Nov 21, 2022
3D mesh stylization driven by a text input in PyTorch

Text2Mesh [Project Page] Text2Mesh is a method for text-driven stylization of a 3D mesh, as described in "Text2Mesh: Text-Driven Neural Stylization fo

Threedle (University of Chicago) 649 Dec 27, 2022
[TPAMI 2021] iOD: Incremental Object Detection via Meta-Learning

Incremental Object Detection via Meta-Learning To appear in an upcoming issue of the IEEE Transactions on Pattern Analysis and Machine Intelligence (T

Joseph K J 66 Jan 04, 2023
Learning where to learn - Gradient sparsity in meta and continual learning

Learning where to learn - Gradient sparsity in meta and continual learning In this paper, we investigate gradient sparsity found by MAML in various co

Johannes Oswald 28 Dec 09, 2022
Pretraining Representations For Data-Efficient Reinforcement Learning

Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch

Mila 40 Dec 11, 2022
Model-based 3D Hand Reconstruction via Self-Supervised Learning, CVPR2021

S2HAND: Model-based 3D Hand Reconstruction via Self-Supervised Learning S2HAND presents a self-supervised 3D hand reconstruction network that can join

Yujin Chen 72 Dec 12, 2022
Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition

Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition The official code of ABINet (CVPR 2021, Oral).

334 Dec 31, 2022
A template repository for submitting a job to the Slurm Cluster installed at the DISI - University of Bologna

Cluster di HPC con GPU per esperimenti di calcolo (draft version 1.0) Per poter utilizzare il cluster il primo passo è abilitare l'account istituziona

20 Dec 16, 2022
EqGAN - Improving GAN Equilibrium by Raising Spatial Awareness

EqGAN - Improving GAN Equilibrium by Raising Spatial Awareness Improving GAN Equilibrium by Raising Spatial Awareness Jianyuan Wang, Ceyuan Yang, Ying

GenForce: May Generative Force Be with You 149 Dec 19, 2022
The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier')

The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography

James 135 Dec 23, 2022
Spherical Confidence Learning for Face Recognition, accepted to CVPR2021.

Sphere Confidence Face (SCF) This repository contains the PyTorch implementation of Sphere Confidence Face (SCF) proposed in the CVPR2021 paper: Shen

Maths 70 Dec 09, 2022
City Surfaces: City-scale Semantic Segmentation of Sidewalk Surfaces

City Surfaces: City-scale Semantic Segmentation of Sidewalk Surfaces Paper Temporary GitHub page for City Surfaces paper. More soon! While designing s

14 Nov 10, 2022
PyTorch Connectomics: segmentation toolbox for EM connectomics

Introduction The field of connectomics aims to reconstruct the wiring diagram of the brain by mapping the neural connections at the level of individua

Zudi Lin 132 Dec 26, 2022
EGNN - Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This

Phil Wang 259 Jan 04, 2023
Painting app using Python machine learning and vision technology.

AI Painting App We are making an app that will track our hand and helps us to draw from that. We will be using the advance knowledge of Machine Learni

Badsha Laskar 3 Oct 03, 2022
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

Ryan Chan 49 Dec 16, 2022
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes

Sungyong Baik 44 Dec 29, 2022
Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.

Deep Image Search - AI-Based Image Search Engine Deep Image Search is an AI-based image search engine that includes deep transfer learning features Ex

139 Jan 01, 2023