Recent News

  • 2019-04-01 : Stereo Blur Dataset initial release
Stereo Blur Dataset / Blurry

Overview

The Stereo Blur Dataset is a large-scale multi-scene dataset for stereo deblurring in dynamic scenes (both indoor and outdoor). It contains 20,637 blurry-sharp stereo images from 135 diverse video clips (480 fps).

  • Training: 17,319 stereo images (98 videos)
  • Testing: 3,318 stereo images (37 videos)
  • Key Features: Large-scale, Multi-scene, Stereo Blur
  • Shot Fashions: Handheld, Fixed, Onboard
  • Camera: ZED Camera (720p, 60fps)
  • Location: Shenzhen, China

Explore the Dataset

Get Started with Stereo Blur Dataset!

Paper

DAVANet: Stereo Deblurring with View Aggregation
  • Shangchen Zhou
  • Jiawei Zhang
  • Wangmeng Zuo
  • Haozhe Xie
  • Jinshan Pan
  • Jimmy Ren

The 2019 Conference on Computer Vision and Pattern Recognition (CVPR 2019)

Team Members