PlantStereo is the first specialized dataset in plant reconstruction and phenotyping based on stereo matching. In terms of data size, PlantStereo exceeds the datasets [26,33,34,35,36,37,39] in early years and is appropriate to be used to train or fine-tune the stereo matching models based on deep learning.
Nov 30, 2021 · In this paper, we aim to address the issue between datasets and models and propose a large scale stereo dataset with high accuracy disparity ground truth named ...
This is the official implementation code for the paper "PlantStereo: A High Quality Stereo Matching Dataset for Plant Reconstruction".
Extensive experiments show that compared with ground truth in integer accuracy, high accuracy disparity images provided by PlantStereo can remarkably ...
In recent years, the accuracy and real-time performance of the stereo matching models have been greatly improved. While the training process relies on ...
Stereo Matching is one of the core technologies in computer vision, which recovers 3D structures of real world from 2D images. It has been widely used in ...
Stereo matching is an important task in computer vision which has drawn tremendous research attention for decades. While in terms of disparity accuracy, ...
PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense Reconstruction. Mingchuan Zhou, Wei Liu, Qingyu Wang, Baojian Ma, Mingzhao Lou, Huanyu Jiang ...
This paper presents a comparative study of six different stereo matching algorithms including Block Matching (BM), Block Matching with Dynamic Programming (BMDP) ...
Stereo matching is a depth perception method for plant phenotyping with high throughput. In recent years, the accuracy and real-time performance of the ...