AI Playground: Unreal Engine-Based Data Ablation Tool for Deep Learning
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Similar racial and gender bias can be observed in an online AI image creator tool Playground AI.
“Similar racial and gender bias can be observed in an online AI image creator tool i.e.Playground AI [56] as exemplified in Figure 4.”
From Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond (2024) · cites this paper as [56]
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404 · see citing works
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126 · see citing works
Playing Atari with Deep Reinforcement Learning
Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., & Riedmiller, M. (2013) · arXiv · doi:10.48550/arxiv.1312.5602 · Cited by 9,471 · see citing works
Indoor segmentation and support inference from rgbd images
Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760 · see citing works
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
Eigen, D., Puhrsch, C., & Fergus, R. (2014) · arXiv · doi:10.48550/arxiv.1406.2283 · Cited by 3,442 · see citing works
Playing for Data: Ground Truth from Computer Games
Richter, S. R., Vineet, V., Roth, S., & Koltun, V. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46475-6_7 · Cited by 1,928 · see citing works
Habitat: A Platform for Embodied AI Research
Savva, M., Kadian, A., Maksymets, O., Zhao, Y., Wijmans, E., Jain, B., Straub, J., Liu, J., Koltun, V., Malik, J., et al. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00943 · Cited by 1,237 · see citing works
VirtualWorlds as Proxy for Multi-object Tracking Analysis
Gaidon, A., Wang, Q., Cabon, Y., & Vig, E. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.470 · Cited by 1,079 · see citing works
High Quality Monocular Depth Estimation via Transfer LearningPreprint
Alhashim, I., & Wonka, P. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1812.11941 · Cited by 479 · see citing works
Ablation Studies in Artificial Neural NetworksPreprint
Meyes, R., Lu, M., de Puiseau, C. W., & Meisen, T. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.08644 · Cited by 358 · see citing works
Virtual Worlds as Proxy for Multi-Object Tracking AnalysisPreprint
Gaidon, A., Wang, Q., Cabon, Y., & Vig, E. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.06457 · Cited by 302 · see citing works
Qiu, W., Zhong, F., Zhang, Y., Qiao, S., Xiao, Z., Kim, T. S., & Wang, Y. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3129396 · Cited by 190 · see citing works
DIODE: A Dense Indoor and Outdoor DEpth DatasetPreprint
Vasiljevic, I., Kolkin, N., Zhang, S., Luo, R., Wang, H., Dai, F. Z., Daniele, A. F., Mostajabi, M., Basart, S., Walter, M. R., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.00463 · Cited by 169 · see citing works
Deep Surface Normal Estimation With Hierarchical RGB-D Fusion
Zeng, J., Tong, Y., Huang, Y., Yan, Q., Sun, W., Chen, J., & Wang, Y. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00631 · Cited by 70 · see citing works
Dynamic Deep Networks for Retinal Vessel Segmentation
Khanal, A., & Estrada, R. G. (2020) · Frontiers in Computer Science · doi:10.3389/fcomp.2020.00035 · Cited by 58 · see citing works
Self-citationFramework for Generation of Synthetic Ground Truth Data for Driver Assistance Applications
Haltakov, V., Unger, C., & Ilić, S. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40602-7_35 · Cited by 57 · see citing works
Model-Driven Simulations for Computer Vision
Veeravasarapu, V. S. R., Rothkopf, C. A., & Visvanathan, R. (2017) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2017.123 · Cited by 12 · see citing works
Randomized Ablation Feature ImportancePreprint
Merrick, L. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.00174 · Cited by 5 · see citing works
Deep Surface Normal Estimation with Hierarchical RGB-D FusionPreprint
Zeng, J., Tong, Y., Huang, Y., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.03405 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [19]19. Weichao Qiu, Fangwei Zhong, Y.Z.S.Q.Z.X.T.S.K.Y.W.A.Y.: Unrealcv: Virtual worlds for computer vision. ACM Multimedia Open Source Software Competition (2017)
Cited by
Sorted by citations
Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond
Nasir, S., Khan, R. A., & Bai, S. (2024) · IEEE Access · doi:10.1109/access.2024.3369912 · Cited by 152 · see citing works
- Authors
- Mousavi, M., Khanal, A., & Estrada, R.
- Affiliations
- Georgia State University (US)
- Corresponding author
- Estrada, Rolando
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 518-532
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3040854202
- Cited by
- 27
- References
- 19
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 8 · 2023: 10 · 2022: 1 · 2021: 2
- FWCI
- 1.00
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Keywords
- Unreal Engine, depth estimation, surface normal estimation, semantic segmentation, object detection, virtual worlds, open source tools
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