DeepAI AI Chat
Log In Sign Up

DAVANet: Stereo Deblurring with View Aggregation

04/10/2019
by   Shangchen Zhou, et al.
0

Nowadays stereo cameras are more commonly adopted in emerging devices such as dual-lens smartphones and unmanned aerial vehicles. However, they also suffer from blurry images in dynamic scenes which leads to visual discomfort and hampers further image processing. Previous works have succeeded in monocular deblurring, yet there are few studies on deblurring for stereoscopic images. By exploiting the two-view nature of stereo images, we propose a novel stereo image deblurring network with Depth Awareness and View Aggregation, named DAVANet. In our proposed network, 3D scene cues from the depth and varying information from two views are incorporated, which help to remove complex spatially-varying blur in dynamic scenes. Specifically, with our proposed fusion network, we integrate the bidirectional disparities estimation and deblurring into a unified framework. Moreover, we present a large-scale multi-scene dataset for stereo deblurring, containing 20,637 blurry-sharp stereo image pairs from 135 diverse sequences and their corresponding bidirectional disparities. The experimental results on our dataset demonstrate that DAVANet outperforms state-of-the-art methods in terms of accuracy, speed, and model size.

READ FULL TEXT

page 1

page 4

page 7

page 8

10/18/2019

Toward 3D Object Reconstruction from Stereo Images

Inferring the 3D shape of an object from an RGB image has shown impressi...
12/09/2018

Monocular and Stereo Cues for Landing Zone Evaluation for Micro UAVs

Autonomous and safe landing is important for unmanned aerial vehicles. W...
09/26/2018

DSR: Direct Self-rectification for Uncalibrated Dual-lens Cameras

With the developments of dual-lens camera modules,depth information repr...
08/21/2019

KeystoneDepth: Visualizing History in 3D

This paper introduces the largest and most diverse collection of rectifi...
10/01/2020

Learned Dual-View Reflection Removal

Traditional reflection removal algorithms either use a single image as i...
07/15/2022

Learning Parallax Transformer Network for Stereo Image JPEG Artifacts Removal

Under stereo settings, the performance of image JPEG artifacts removal c...
11/28/2017

Highlighting objects of interest in an image by integrating saliency and depth

Stereo images have been captured primarily for 3D reconstruction in the ...