COD-Rank-Localize-and-Segment (CVPR2021)

Overview

COD-Rank-Localize-and-Segment (CVPR2021)

Simultaneously Localize, Segment and Rank the Camouflaged Objects alt text alt text

Full camouflage fixation training dataset is available!

The full camouflage fixation training dataset is available with the full fixation maps for the COD10K training dataset, which can be downloaded from: https://drive.google.com/file/d/1inb5iNTDswFPDm4SpzBbVgZdI4puAv_3/view?usp=sharing

Camouflage Localization and Ranking dataset

We labeled the COD10K training dataset with eye tracker to localize the camouflaged objects, and generate 2000 images with localization and ranking label (We are generating fixation and label for all the existing training and testing dataset, and will release the dataset very soon.). The training dataset is as:

https://drive.google.com/file/d/12kSU6QrPAiumWpSkMqi5nPMo1awBW0_N/view?usp=sharing

which include 2000 images, with the corresponding fixation label, ranking label and instance level labels.

The testing dataset is as:

https://drive.google.com/file/d/1Gz5GzL9eeW13aZjlzaisrJFGO-HmhLxS/view?usp=sharing

which include 280 images with fixation, ranking and instance level labels.

Our Results

We train our triple-task learning framework with the above 2000 image training dataset and show the results in Table 1 of the main paper. The resulted camouflage maps are as:

https://drive.google.com/file/d/1ahu77JP-hzjgup20fNIftCB_cHanE323/view?usp=sharing

We also train our camouflaged object detection task along with the original COD10K training dataset, and show the performance in Table 4. The resulted camouflage maps are as:

https://drive.google.com/file/d/10sr2lX38FEgSXL3k27gidlaPKo5VQyjv/view?usp=sharing

Note that, we re-train our models, and the resulted performance is slightly difference from our reported numbers.

Benchmark results:

  1. Please download the benchmark results (camoudlage maps) for your convienience. All the benchmark methods are trained with the COD10K training dataset (of size 4040):

https://drive.google.com/drive/folders/1sdly_TFW2WVqSm-hzuVXYKnu3DxkF-0F?usp=sharing

  1. Or the computed evaluation metrics:

https://drive.google.com/file/d/17SyikbvnNF6g0_2BteyplQLid2o0KZTc/view?usp=sharing

New dataset: NC4K

Please download our newly collected camouflaged object detection testing dataset, namely NC4K, in the link below (with image, ground truth map, and instance level annotation): https://drive.google.com/file/d/1kzpX_U3gbgO9MuwZIWTuRVpiB7V6yrAQ/view?usp=sharing

or please download it from BaiduNetDisk: 链接:https://pan.baidu.com/s/1bG4F2KJ_4UJG_7XG6ZNBHA 密码:d581

Our Bib:

Please cite our paper if necessary:

@inproceedings{yunqiu_cod21,
  title={Simultaneously Localize, Segment and Rank the Camouflaged Objects},
  author={Lyu, Yunqiu and Zhang, Jing and Dai, Yuchao and Li, Aixuan and Liu, Bowen and Barnes, Nick and Fan, Deng-Ping},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021}
}

Contact

Please drop me an email for further problems or discussion: [email protected]

Owner
JingZhang
PhD Candidate
JingZhang
Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification

Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification Usage The required packages are lis

0 Feb 07, 2022
Official PyTorch implementation of Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations

Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, Kuan Fang, Yu

UT-Austin Robot Perception and Learning Lab 63 Jan 03, 2023
Supplementary code for SIGGRAPH 2021 paper: Discovering Diverse Athletic Jumping Strategies

SIGGRAPH 2021: Discovering Diverse Athletic Jumping Strategies project page paper demo video Prerequisites Important Notes We suspect there are bugs i

54 Dec 06, 2022
PyTorch implementation(s) of various ResNet models from Twitch streams.

pytorch-resnet-twitch PyTorch implementation(s) of various ResNet models from Twitch streams. Status: ResNet50 currently not working. Will update in n

Daniel Bourke 3 Jan 11, 2022
A simple pytorch pipeline for semantic segmentation.

SegmentationPipeline -- Pytorch A simple pytorch pipeline for semantic segmentation. Requirements : torch=1.9.0 tqdm albumentations=1.0.3 opencv-pyt

petite7 4 Feb 22, 2022
Development of IP code based on VIPs and AADM

Sparse Implicit Processes In this repository we include the two different versions of the SIP code developed for the article Sparse Implicit Processes

1 Aug 22, 2022
Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

CSRL Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning Python: 3

4 Apr 14, 2022
Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.

PHDimGeneralization Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021. Overvie

Tolga Birdal 13 Nov 08, 2022
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling Transformer-based models are widely used in natural language processi

Zhanpeng Zeng 12 Jan 01, 2023
Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation

Auto-Seg-Loss By Hao Li, Chenxin Tao, Xizhou Zhu, Xiaogang Wang, Gao Huang, Jifeng Dai This is the official implementation of the ICLR 2021 paper Auto

61 Dec 21, 2022
Unofficial PyTorch implementation of Google AI's VoiceFilter system

VoiceFilter Note from Seung-won (2020.10.25) Hi everyone! It's Seung-won from MINDs Lab, Inc. It's been a long time since I've released this open-sour

MINDs Lab 883 Jan 07, 2023
CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images

CFC-Net This project hosts the official implementation for the paper: CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Dete

ming71 55 Dec 12, 2022
Weight estimation in CT by multi atlas techniques

maweight A Python package for multi-atlas based weight estimation for CT images, including segmentation by registration, feature extraction and model

György Kovács 0 Dec 24, 2021
Spatial Transformer Nets in TensorFlow/ TensorLayer

MOVED TO HERE Spatial Transformer Networks Spatial Transformer Networks (STN) is a dynamic mechanism that produces transformations of input images (or

Hao 36 Nov 23, 2022
PyTorch-centric library for evaluating and enhancing the robustness of AI technologies

Responsible AI Toolbox A library that provides high-quality, PyTorch-centric tools for evaluating and enhancing both the robustness and the explainabi

24 Dec 22, 2022
Code for NeurIPS 2020 article "Contrastive learning of global and local features for medical image segmentation with limited annotations"

Contrastive learning of global and local features for medical image segmentation with limited annotations The code is for the article "Contrastive lea

Krishna Chaitanya 152 Dec 22, 2022
Compact Bidirectional Transformer for Image Captioning

Compact Bidirectional Transformer for Image Captioning Requirements Python 3.8 Pytorch 1.6 lmdb h5py tensorboardX Prepare Data Please use git clone --

YE Zhou 19 Dec 12, 2022
[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
Extension to fastai for volumetric medical data

FAIMED 3D use fastai to quickly train fully three-dimensional models on radiological data Classification from faimed3d.all import * Load data in vari

Keno 26 Aug 22, 2022
Complete system for facial identity system. Include one-shot model, database operation, features visualization, monitoring

Complete system for facial identity system. Include one-shot model, database operation, features visualization, monitoring

2 Dec 28, 2021