activity
20182020
collaborators

6 papers

cs.CV2020

Ellipse R-CNN: Learning to Infer Elliptical Object from Clustering and Occlusion

Wenbo Dong, Pravakar Roy, Cheng Peng +1

Images of heavily occluded objects in cluttered scenes, such as fruit clusters in trees, are hard to segment. To further retrieve the 3D size and 6D pose of each individual object…

cs.CV2019

MinneApple: A Benchmark Dataset for Apple Detection and Segmentation

Nicolai Häni, Pravakar Roy, Volkan Isler

In this work, we present a new dataset to advance the state-of-the-art in fruit detection, segmentation, and counting in orchard environments. While there has been significant rece…

cs.CV2019

Semantics-Aware Image to Image Translation and Domain Transfer

Pravakar Roy, Nicolai Häni, Jun-Jee Chao +1

Image to image translation is the problem of transferring an image from a source domain to a different (but related) target domain. We present a new unsupervised image to image tra…

cs.CV2018

A Comparative Study of Fruit Detection and Counting Methods for Yield Mapping in Apple Orchards

Nicolai Häni, Pravakar Roy, Volkan Isler

We present new methods for apple detection and counting based on recent deep learning approaches and compare them with state-of-the-art results based on classical methods. Our goal…

cs.RO2018

Semantic Mapping for Orchard Environments by Merging Two-Sides Reconstructions of Tree Rows

Wenbo Dong, Pravakar Roy, Volkan Isler

Measuring semantic traits for phenotyping is an essential but labor-intensive activity in horticulture. Researchers often rely on manual measurements which may not be accurate for…

cs.CV2018

Vision-Based Preharvest Yield Mapping for Apple Orchards

Pravakar Roy, Abhijeet Kislay, Patrick A. Plonski +2

We present an end-to-end computer vision system for mapping yield in an apple orchard using images captured from a single camera. Our proposed system is platform independent and do…