Workshop Programme

Half day workshop, Monday morning June 17. Location: Hyatt Regency F (fourth floor).

Posters will be in the Pacific Arena Ballroom (main convention center).

Full papers as well as extended abstracts have posters. Selected full papers in addition present oral spotlights. Full papers are published in the CVPR workshop proceedings. Extended abstracts are published below.

11:15 Keynote by Victor Lempitsky:
New Single-Stage Approaches to Instance Segmentation

Instance segmentation is a key computer vision task for plant phenotyping. Two-stage systems that perform instance segmentation using object detection followed by object mask estimation (such as Mask-RCNN) have been hugely successful. At the same time, there is an interest in the community in single-stage instance segmentation methods that solve the same task by labeling individual pixels akin to semantic segmentation. Such single-stage approaches are much simpler and more computationally efficient. Yet they need to solve an intricate problem of choosing the pixel label set that can successfully encode the instance segmentation task while being amenable for training. In this talk, I will discuss two new single-stage approaches to instance segmentation that use two different label spaces and loss functions, and both achieve competitive results on several tasks including leave segmentation tasks in plant phenotyping. This is joint work with Victor Kulikov and Victor Yurchenko.

Programme

08:00 Registration and hanging posters

08:15 Welcome

08:30 Oral Session: Spotlights (Hyatt Regency F)

• Adversarial Large-scale Root Gap Inpainting     

Hao Chen, Mario Valerio Giuffrida, Peter Doerner, Sotirios Tsaftaris

• Leaf Segmentation by Functional Modeling

Yuhao Chen, Sriram Baireddy Enyu Cai, Changye Yang, Edward Delp

• Prediction of Sorghum Biomass Using UAV Time Series Data and Recurrent Neural Networks

Ali Masjedi, Neal Carpenter, Melba Crawford, Mitch Tuinstra

• ProTractor: a lightweight ground imaging and analysis system for early-season field phenotyping

Nico Higgs, Blanche Leyeza, Jordan Ubbens, Josh Kocur, William van der Kamp, Theron Cory, Christina Eynck, Sally Vail, Mark Eramian, Ian Stavness

• The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture

Søren Skovsen, Mads MD Dyrmann, Anders K Mortensen, Morten Stigaard Laursen, René Gislum, Jørgen Eriksen, Sadaf Farkhani, Henrik Karstoft, Rasmus Nyholm Jørgensen

• The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation

Anders K Mortensen, Søren Skovsen, Henrik Karstoft, René Gislum

09:30 Poster Session [coffee break is 10:00 – 10:45] (Pacific Arena Ballroom)

11:15 Invited Keynote Talk (Hyatt Regency F)

• New Single-Stage Approaches to Instance Segmentation

Victor Lempitsky

12:00 Closing Remarks / Awards / Discussion

12:15 End

Posters

Location: Pacific Arena Ballroom (main convention center). Poster board numbers are given in brackets.

PDFs of full papers can be found at the official CVPR webpage. Extended abstracts are linked directly.

1. [#244] Leaf Segmentation by Functional Modeling
• Yuhao Chen, Sriram Baireddy Enyu Cai, Changye Yang, Edward Delp
2. [#245] Prediction of Sorghum Biomass Using UAV Time Series Data and Recurrent Neural Networks
• Ali Masjedi, Neal Carpenter, Melba Crawford, Mitch Tuinstra
3. [#246] ProTractor: a lightweight ground imaging and analysis system for early-season field phenotyping
• Nico Higgs, Blanche Leyeza, Jordan Ubbens, Josh Kocur, William van der Kamp, Theron Cory, Christina Eynck, Sally Vail, Mark Eramian, Ian Stavness
4. [#247] The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture
• Søren Skovsen, Mads MD Dyrmann, Anders K Mortensen, Morten Stigaard Laursen, René Gislum, Jørgen Eriksen, Sadaf Farkhani, Henrik Karstoft, Rasmus Nyholm Jørgensen
5. [#248] The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation
• Anders K Mortensen, Søren Skovsen, Henrik Karstoft, René Gislum
6. [#249] Adversarial Large-scale Root Gap Inpainting     
• Hao Chen, Mario Valerio Giuffrida, Peter Doerner, Sotirios Tsaftaris
7. [#250] Leaf Counting Without Annotations Using Adversarial Unsupervised Domain Adaptation
• Mario Valerio Giuffrida, Andrei Dobrescu, Peter Doerner, Sotirios Tsaftaris
8. [#251] Understanding Deep Neural Networks for Regression in Leaf Counting     
• Andrei Dobrescu, Mario Valerio Giuffrida, Sotirios Tsaftaris
9. [#252] Leaf counting from uncontrolled acquired images from greenhouse workers
• João Valente, Mario Valerio Giuffrida
10. [#253] Data augmentation from RGB to chlorophyll fluorescence imaging Application to leaf segmentation of Arabidopsis thaliana from top view images         
• Natalia Sapoukhina, Salma Samiei, Pejman Rasti, David Rousseau
11. [#254] Length Phenotyping with Interest Point Detection     
• Adar Vit, Guy Shani, Aharon Bar-Hillel
12. [#255] Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks
• Laura Zabawa, Anna Kicherer, Lasse Klingbeil, Andres L Milioto, Reinhard Töpfer, Heiner Kuhlmann, Ribana Roscher
13. [#256] Data Augmentation for Leaf Segmentation and Counting Tasks in Rosette Plants     
• Dmitry Kuznichov, Alon Zvirin, Yaron Honen, Ron Kimmel
14. [#257] A guided multi-scale categorization of plant species in natural images     
• Jonas Krause, Kyungim Baek, Lipyeow Lim
15. [#258] ROLS: Robust Object-level SLAM for grape counting    
• Anjana Kakecochi Nellithimaru, George Kantor
16. [#259] Crop Lodging Prediction from UAV-Acquired Images of Wheat and Canola using a DCNN Augmented with Handcrafted Texture Features     
• Sara Mardanisamani, Farhad Maleki, Sara Hosseinzadeh Kassani, Sajith Rajapaksa, Hema Duddu, Menglu Wang, Steve Shirtliffe, Seungbum Ryu, Anique Josuttes, Ti Zhang, Sally Vail, Curtis Pozniak, Isobel Parkin, Ian Stavness, Mark Eramian
17. [#260] Bean Split Ratio for Dry Bean Canning Quality and Variety Analysis     
• Yunfei Long, Amber Bassett, Karen Cichy, Addie Thompson, Daniel Morris
18. [#261] VisND: A Visualization Tool for Multidimensional Model of Canopy     
• Ali Shafiekhani, Felix B. Fritschi, Guilherme DeSouza
19. [#262] Cost-effective, high-throughput 3D reconstruction method for fruit phenotyping
• Mitchell Feldmann, Amy Tabb, Steven Knapp
20. [#263] Visualizing Data Driven Phenotypes
• Zeyu Zhang, Xiaotong Liu, Hong Xuan, Abby Stylianou, Robert Pless
21. [#264] Learning to Correct for Bad Camera Settings in Large Scale Plant Monitoring
• Zongyang Li, Abby Stylianou, Robert Pless
22. [#265] Multi-View Instance Matching for Plant Leaf Modeling
• Takuma Doi, Fumio Okura, Yasuyuki Matsushita, Yasushi Yagi
23. [#266] Plant segmentation and leaf labelling using chlorophyll fluorescence images
• Augusto Cesar Magalhaes de Souza, Yang Yang
24. [#267] Web-based Annotation tool for Image-based Phenotyping
• Jialin Yuan, Zheng Zhou, Michael Nagle, Peremyslova Ekaterina, Nihar Doshi, Ritesh Mewalal, Cathleen Ma, Steve Strauss, Li Fuxin
25. [#268] Using Active Learning to Reduce Training Data in Deep-learning-based Flower Classification
• Feng Chen, Andrew P French, Tony Pridmore
26. [#269] UAV Based Remote Sensing for Tassel Detection and Growth Stage Estimation of Maize Crop using F-RCNN
• Ajay Kumar, Mahesh Taparia, Wei Guo, Rajalakshmi Pachamuthu, Balaji Naik Banothu, Uday B. Desai
27. [#270] DNN-Based Tiller Number Estimation for Coping with Shortage of Labeled Data
• Yuzuko Utsumi, Koichiro Nakamura, Masakazu Iwamura, Koichi Kise
28. [#271] Hierarchical multi-label Classification of Plant Images using Convolutional Neural Network
• Mads MD Dyrmann, Søren Skovsen, Rasmus Nyholm Jørgensen