An official implementation of "Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation" (ICCV 2021) in PyTorch.

Related tags

Deep LearningJoEm
Overview

Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation

This is an official implementation of the paper "Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation", accepted to ICCV2021.

For more information, please checkout the project site [website] and the paper [arXiv].

Pre-requisites

This repository uses the following libraries:

  • Python (3.6)
  • Pytorch (1.8.1)

Getting Started

Datasets

VOC

The structure of data path should be organized as follows:

/dataset/PASCALVOC/VOCdevkit/VOC2012/                         % Pascal VOC datasets root
/dataset/PASCALVOC/VOCdevkit/VOC2012/JPEGImages/              % Pascal VOC images
/dataset/PASCALVOC/VOCdevkit/VOC2012/SegmentationClass/       % Pascal VOC segmentation maps
/dataset/PASCALVOC/VOCdevkit/VOC2012/ImageSets/Segmentation/  % Pascal VOC splits

CONTEXT

The structure of data path should be organized as follows:

/dataset/context/                                 % Pascal CONTEXT dataset root
/dataset/context/59_labels.pth                    % Pascal CONTEXT segmentation maps
/dataset/context/pascal_context_train.txt         % Pascal CONTEXT splits
/dataset/context/pascal_context_val.txt           % Pascal CONTEXT splits
/dataset/PASCALVOC/VOCdevkit/VOC2012/JPEGImages/  % Pascal VOC images

Training

We use DeepLabV3+ with ResNet-101 as our visual encoder. Following ZS3Net, ResNet-101 is initialized with the pre-trained weights for ImageNet classification, where training samples of seen classes are used only. (weights here)

VOC

python train_pascal_zs3setting.py -c configs/config_pascal_zs3setting.json -d 0,1,2,3

CONTEXT

python train_context_zs3setting.py -c configs/config_context_zs3setting.json -d 0,1,2,3

Testing

VOC

python train_pascal_zs3setting.py -c configs/config_pascal_zs3setting.json -d 0,1,2,3 -r <visual encoder>.pth --test

CONTEXT

python train_pascal_zs3setting.py -c configs/config_pascal_zs3setting.json -d 0,1,2,3 -r <visual encoder>.pth --test

Acknowledgements

You might also like...
Official implementation of NPMs: Neural Parametric Models for 3D Deformable Shapes - ICCV 2021
Official implementation of NPMs: Neural Parametric Models for 3D Deformable Shapes - ICCV 2021

NPMs: Neural Parametric Models Project Page | Paper | ArXiv | Video NPMs: Neural Parametric Models for 3D Deformable Shapes Pablo Palafox, Aljaz Bozic

PabloPalafox 109 Nov 22, 2022
Official implementation of the paper Vision Transformer with Progressive Sampling, ICCV 2021.
Official implementation of the paper Vision Transformer with Progressive Sampling, ICCV 2021.

Vision Transformer with Progressive Sampling This is the official implementation of the paper Vision Transformer with Progressive Sampling, ICCV 2021.

yuexy 123 Jan 1, 2023
Official implementation of the ICCV 2021 paper
Official implementation of the ICCV 2021 paper "Conditional DETR for Fast Training Convergence".

The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings and that the spatial embeddings make minor contributions, increasing the need for high-quality content embeddings and thus increasing the training difficulty.

null 281 Dec 30, 2022
The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.
The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.

SCOOD-UDG (ICCV 2021) This repository is the official implementation of the paper: Semantically Coherent Out-of-Distribution Detection Jingkang Yang,

Jake YANG 62 Nov 21, 2022
Official implementation of the ICCV 2021 paper:
Official implementation of the ICCV 2021 paper: "The Power of Points for Modeling Humans in Clothing".

The Power of Points for Modeling Humans in Clothing (ICCV 2021) This repository contains the official PyTorch implementation of the ICCV 2021 paper: T

Qianli Ma 158 Nov 24, 2022
Official implementation of the ICCV 2021 paper
Official implementation of the ICCV 2021 paper "Joint Inductive and Transductive Learning for Video Object Segmentation"

JOINT This is the official implementation of Joint Inductive and Transductive learning for Video Object Segmentation, to appear in ICCV 2021. @inproce

Yunyao 35 Oct 16, 2022
[ICCV 2021] Official Tensorflow Implementation for
[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"

KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl

Hyeongseok Son 50 Dec 29, 2022
Official implementation of Protected Attribute Suppression System, ICCV 2021

Official implementation of Protected Attribute Suppression System, ICCV 2021

Prithviraj Dhar 6 Jan 1, 2023
Official Pytorch Implementation of 'Learning Action Completeness from Points for Weakly-supervised Temporal Action Localization' (ICCV-21 Oral)
Official Pytorch Implementation of 'Learning Action Completeness from Points for Weakly-supervised Temporal Action Localization' (ICCV-21 Oral)

Learning-Action-Completeness-from-Points Official Pytorch Implementation of 'Learning Action Completeness from Points for Weakly-supervised Temporal A

Pilhyeon Lee 67 Jan 3, 2023
Comments
  • datasets

    datasets

    Thank you for your work～

    self._cat_dir = self._base_dir / ("%d_labels.pth" % (self.n_categories))

    Could you tell me how to generate the "59_labels.pth" file of the context dataset?

    opened by Wangyiqi 1
  • train_aug.txt

    train_aug.txt

    Dear Authors,

    When I run your code, there is an error:

    FileNotFoundError: [Errno 2] No such file or directory: 'dataset/PASCALVOC/VOCdevkit/VOC2012/ImageSets/Segmentation/train_aug.txt'

    Could you tell me how to get train_aug.txt?

    opened by AmingWu 1
  • dataset split

    dataset split

    After introducing the SBD (Semantic Boundary Dataset), what kind of split (train_split and test_split include how many images ) is adopted by this paper?

    opened by zaiquanyang 0
Owner
CV Lab @ Yonsei University
CV Lab @ Yonsei University
GitHub Repository
Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation

SUO-SLAM This repository hosts the code for our CVPR 2022 paper "Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation". ArXiv li

Robot Perception & Navigation Group (RPNG) 97 Jan 03, 2023
Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research) This is a PyTorch implementation of the CoMatch paper [B

Salesforce 107 Dec 14, 2022
A curated list of awesome Active Learning

Awesome Active Learning 🤩 A curated list of awesome Active Learning ! 🤩 Background (image source: Settles, Burr) What is Active Learning? Active lea

BAI Fan 431 Jan 03, 2023
Lama-cleaner: Image inpainting tool powered by LaMa

Lama-cleaner: Image inpainting tool powered by LaMa

Qing 5.8k Jan 05, 2023
GNN-based Recommendation Benchmark

GRecX A Fair Benchmark for GNN-based Recommendation Homepage and Documentation Homepage: Documentation: Paper: GRecX: An Efficient and Unified Benchma

73 Oct 17, 2022
VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech Jaehyeon Kim, Jungil Kong, and Juhee Son In our rece

Jaehyeon Kim 1.7k Jan 08, 2023
MPI-IS Mesh Processing Library

Perceiving Systems Mesh Package This package contains core functions for manipulating meshes and visualizing them. It requires Python 3.5+ and is supp

Max Planck Institute for Intelligent Systems 494 Jan 06, 2023
Code for the ICCV2021 paper "Personalized Image Semantic Segmentation"

PSS: Personalized Image Semantic Segmentation Paper PSS: Personalized Image Semantic Segmentation Yu Zhang, Chang-Bin Zhang, Peng-Tao Jiang, Ming-Ming

张宇 15 Jul 09, 2022
Official Pytorch Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images.

IAug_CDNet Official Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images. Overview We propose a

53 Dec 02, 2022
Official implementation of paper Gradient Matching for Domain Generalization

Gradient Matching for Domain Generalisation This is the official PyTorch implementation of Gradient Matching for Domain Generalisation. In our paper,

94 Dec 23, 2022
Predict bus arrival time using VertexAI and Nvidia's Jetson Nano

bus_prediction predict bus arrival time using VertexAI and Nvidia's Jetson Nano imagenet the command for imagenet.py look like this python3 /path/to/i

10 Dec 22, 2022
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification [pdf] The official repository for Self-Supervised Pre-Training for Transfo

Hao Luo 116 Jan 04, 2023
💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena

💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena.

Heidelberg-NLP 17 Nov 07, 2022
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"

GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context

P-Lambda 29 Dec 19, 2022
YOLOX-Paddle - A reproduction of YOLOX by PaddlePaddle

YOLOX-Paddle A reproduction of YOLOX by PaddlePaddle 数据集准备 下载COCO数据集，准备为如下路径 /ho

QuanHao Guo 6 Dec 18, 2022
Repository for MDPGT

MD-PGT Repository for implementing and reproducing the results for the paper MDPGT: Momentum-based Decentralized Policy Gradient Tracking. Available E

Xian Yeow Lee 2 Dec 30, 2021
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects

[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here:

Denys Rozumnyi 107 Dec 26, 2022
Tool for live presentations using manim

manim-presentation Tool for live presentations using manim Install pip install manim-presentation opencv-python Usage Use the class Slide as your sce

Federico Galatolo 146 Jan 06, 2023
This code is an unofficial implementation of HiFiSinger.

HiFiSinger This code is an unofficial implementation of HiFiSinger. The algorithm is based on the following papers: Chen, J., Tan, X., Luan, J., Qin,

Heejo You 87 Dec 23, 2022
An investigation project for SISR.

SISR-Survey An investigation project for SISR. This repository is an official project of the paper "From Beginner to Master: A Survey for Deep Learnin

Juncheng Li 79 Oct 20, 2022