https://github.com/Heart-eartH/MVSalNet

https://github.com/Heart-eartH/MVSalNet

Last synced: 3 months ago
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• Host: GitHub
• URL: https://github.com/Heart-eartH/MVSalNet
• Owner: Heart-eartH
• License: mit
• Created: 2022-07-20T02:23:25.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-08-08T17:11:46.000Z (11 months ago)
• Last Synced: 2024-01-17T04:03:51.130Z (6 months ago)
• Language: Python
• Size: 2.09 MB
• Stars: 10
• Watchers: 1
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-salient-object-detection - Code

README

        
# MVSalNet

(ECCV2022)MVSalNet:Multi-View Augmentation for RGB-D Salient Object Detection

Jiayuan Zhou1, Lijun Wang1, Huchuan Lu1,2, Kaining Huang3, Xinchu Shi3 , Bocong Liu3

1 Dalian University of Technology

2 Peng Cheng Laboratory

3 Meituan

The code of MVSalNet in ECCV2022

[Results(password:yydz)](https://pan.baidu.com/s/1ZwWBvH0GhRxdsT02CMvGqg) 

## Motivations

The depth map and RGB images are from two different modalities with significant cross-modal gap.

The 3D geometry contained in depth map can be used to render the input image under different views.

## Our Contributions

We present a new framework for RGB-D SOD with multi-view augmentation, which can effectively leverage the geometry information carried in input depth maps.

We design a multi-view saliency prediction network with dynamic filtering modules, which can not only enhance saliency prediction in each single view, but also enables cross-view prediction fusion, yielding more accurate SOD results.

## Multi-View Data Augmentation

Reconstruct the 3D point cloud based on the input scene depth.

Project the point cloud to a specific target view to render the RGB image.



## Multi-View Saliency Detection Network

Single-view saliency prediction module

Multi-view fusion module



## Visual Comparisons



## Brief Summary

A new RGB-D salient object detection (SOD) framework to take full advantages of 3D geometry information contained in depth maps.

A multi-view salient detection network (MVSalNet).

Experiments on six popular benchmarks verify the effectiveness.