fcdl94

MiB

Official code for Modeling the Background for Incremental Learning in Semantic Segmentation https://arxiv.org/abs/2002.00718

WILSON

Official implementation of "Incremental Learning in Semantic Segmentation from Image Labels"

CoMFormer

Official implementation of "CoMFormer: Continual Learning in Semantic and Panoptic Segmentation"

FSS

Prototype-based Incremental Few-Shot Semantic Segmentation

MMA

Modeling Missing Annotations for Incremental Learning in Object Detection

MiBv2

New Modeling The Background CodeBase

EWC

OnlineEWC and EWC++ implementations, the online versions of Elastic weight consolidation

RobotChallenge

ICL

Incremental Class Learning project

Multi-Domain-Learning

visda-2019-public

CodebaseSemSeg

fcdl94.github.io

[Check the website](http://fcdl94.github.io)

1-stage-wseg

Single-Stage Semantic Segmentation from Image Labels (CVPR 2020)

awesome-zero-shot-learning

A curated list of papers, code and resources pertaining to zero shot learning

BiseNetv1

Code for BiseNetV1

detectron2

Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.

Mask2Former

Code release for "Masked-attention Mask Transformer for Universal Image Segmentation"

MECHack

RL_methods

In this repository I will experiment with some well-known RL methods.

SPNet

Semantic Projection Network for Zero- and Few-Label Semantic Segmentation

SSD

Repository for Single Shot MultiBox Detector and its variants, implemented with pytorch, python3.

UDA

This repo contains the code of some methods of unsupervised domain adaptation

detr

End-to-End Object Detection with Transformers

EPS

Official PyTorch implementation of "Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation", CVPR2021

kmax-deeplab

Detectron2: k-means mask Transformer.

Laboratorio_Scolastico

Provide files for PXE in school lab.

pyTorchExamples

Some trivial and getting started examples with PyTorch

VehicleTracking

DP2 Project of 2017

YOSO

You Only Segment Once: Towards Real-Time Panoptic Segmentation