ProcSy: Procedural Synthetic Dataset Generation Towards Influence Factor Studies Of Semantic Segmentation Networks

By Samin Rahman Khan, Buu Phan, Rick Salay, Krzysztof Czarnecki. 2019

49 citations recorded by the source corpus.

Subfields: 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 Computer Vision and Pattern Recognition

1. Nathan Paczan
2. Mike Roberts
3. Sergey I. Nikolenko
4. Amir Zamir
5. Roman Bachmann
6. Jitendra Malik

In Evaluation & Benchmarks

1. Sergey I. Nikolenko
2. Nathan Paczan
3. Mike Roberts
4. Amir Zamir
5. Roman Bachmann

Citations in the corpus

• Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding (2020, background): “No existing synthetic dataset or simulator addresses all of these limitations, including those that have been developed for outdoor scene understanding [7, 18, 21, 32, 36, 39, 53, 54, 55, 56, 61, 72, 73].”
• Synthetic Data for Deep Learning (2019, methodology): “Figure 1: Sample images: (a-c) MS COCO [363] real data samples with ground truth segmentation maps overlaid; (d-e) ProcSy [317]: (d) RGB image, (e) ground truth segmentation map.”