Quality Assessment for Crowdsourced Object Annotations
By Sirion Vittayakorn, James Hays. 2011
29 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Evaluation & Benchmarks
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Li Fei-Fei
- Trevor Darrell
- Jia Deng
- Devi Parikh
- Marcus Rohrbach
- Mohit Bansal
- Olga Russakovsky
- Alexander C. Berg
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Trevor Darrell
- Dacheng Tao
- Xiaogang Wang
- Li Fei-Fei
- Andrea Vedaldi
- Andrew Zisserman
- Jitendra Malik
In Evaluation & Benchmarks
- Li Fei-Fei
- Trevor Darrell
- Andrea Vedaldi
- Alan L. Yuille
- Kaiming He
- Abhinav Kumar Gupta
- Yi Yang
- Olga Russakovsky
Citations in the corpus
- ImageNet Large Scale Visual Recognition Challenge (2014, background): “Works such as (Welinder et al., 2010; Sheng et al., 2008; Vittayakorn and Hays, 2011) describe quality control mechanisms for this marketplace.”
- Crowdsourcing in Computer Vision (2016, unknown): “Efforts such as [Russell et al., 2007, Vittayakorn and Hays, 2011] have additionally investigated automatic grading procedures to estimate annotation quality in a complex task: for example, counting the number of vertices in an annotated polygon around an object instance can serve as a proxy of…”
- Boundary Detection Benchmarking: Beyond F-Measures (2013, unknown): “Specifically, [24] has proposed strategies to estimate the quality of crowdsourced boundary annotation.”