Granted Patent
B1
US 12,718,380 · App. 17/686,893 · Granted Aug 25, 2026
Image segmentation using deep neural networks
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Assignments (3)
SECURITY INTEREST
Recorded Jun 24, 2026
From: UPWORK INC.
To: BANK OF AMERICA, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 075067/0544 →
ASSIGNMENT OF ASSIGNOR'S INTEREST
Recorded Jan 18, 2024
From: HEADROOM, INC.
To: UPWORK INC.
Reel/Frame 066163/0044 →
ASSIGNMENT OF ASSIGNOR'S INTEREST
Recorded Jan 25, 2023
From: HARDY, MEGAN; RABINOVICH, ANDREW
To: HEADROOM, INC.
Reel/Frame 062489/0754 →
Continuity (1)
Provisional Application
63157607
· Mar 5, 2021
References Cited (52)
US 20130101002A1
· Gettings
· 2013
[cited by applicant]
US 20210150278A1
· Dudzik
· 2021
[cited by examiner]
US 20250209627A1
· Yeh
· 2025
[cited by examiner]
Yulin Wang: Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification (Year: 2020).
[cited by examiner]
Cai et al., “Disentangled image matting,” Proceedings of the IEEE International Conference on Computer Vision, Oct. 2019, pp. 8819-8828.
[cited by applicant]
Chen et al., “Semantic human matting,” Proceedings of the 26th ACM International Conference on Multimedia, Oct. 2018, pp. 618-626.
[cited by applicant]
Cho et al., “Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation,” arXiv, Sep. 3, 2014, 15 pages.
[cited by applicant]
Elman, “Finding structure in time,” Cognitive Science, Mar. 1990, 14(2): 179-211.
[cited by applicant]
Fan et al., “Shifting more attention to video salient object detection,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun. 2019, pp. 8554-8564.
[cited by applicant]
He et al., “Deep residual learning for image recognition,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jun. 2016, pp. 770-778.
[cited by applicant]
Hochreiter et al., “Long short-term memory,” Neural Computation, Nov. 15, 1997, 9(8):1735-1780.
[cited by applicant]
Hochreiter, “Untersuchungen zu dynamischen neuronalen netzen,” Thesis for the degree of Master's, Technische Universitat Munchen, Institut fur Informatik, Jun. 15, 1991, 91(1), 125 pages (with machine translation).
[cited by applicant]
Hou et al., “Deeply supervised salient object detection with short connections,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jul. 2017, pp. 3203-3212.
[cited by applicant]
Hu et al., “Recurrently aggregating deep features for salient object detection,” Proceedings of the AAAI Conference on Artificial Intelligence, Apr. 27, 2018, 32(1):6943-6950.
[cited by applicant]
Huang et al., “Densely connected convolutional networks,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jul. 2017, pp. 4700-4708.
[cited by applicant]
Ke et al., “Is a green screen really necessary for real-time human matting?,” arXiv, Nov. 24, 2020, 11 pages.
[cited by applicant]
Li et al., “End-to-end animal image matting,” arXiv, Oct. 30, 2020, 14 pages.
[cited by applicant]
Li et al., “Visual saliency based on multiscale deep features,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2015, pp. 5455-5463.
[cited by applicant]
Lin et al., “Real-time high-resolution background matting,” arXiv, Dec. 14, 2020, 16 pages.
[cited by applicant]
Liu et al. “A simple pooling-based design for real-time salient object detection,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jun. 2019, pp. 3917-3926.
[cited by applicant]
Liu et al. “Picanet: Pixel-wise contextual attention learning for accurate saliency detection,” IEEE Transactions on Image Processing, Apr. 2020, 13 pages.
[cited by applicant]
Liu et al., “Parsenet: Looking wider to see better,” arXiv, Nov. 19, 2015, 11 pages.
[cited by applicant]
Long et al., “Fully convolutional networks for semantic segmentation, ” Proceedings of the IEEE Conference on Computer Vision and Pattern recognition, Jun. 2015, pp. 3431-3440.
[cited by applicant]
Lu et al. “Robust and efficient saliency modeling from image co-occurrence histograms,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Jan. 2014, 36(1):195-201.
[cited by applicant]
Lu et al., “Saliency modeling from image histograms,” Presented at 12th European Conference on Computer Vision, Florence, Italy, Oct. 7-13, 2012, pp. 321-332.
[cited by applicant]
Perazzi et al., “Saliency filters: Contrast based filtering for salient region detection,” Presented at 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA, Jun. 16-21, 2012, pp. 733-740.
[cited by applicant]
Qin et al. “U2-net: Going deeper with nested u-structure for salient object detection,” Pattern Recognition, Oct. 2020, 106:107404.
[cited by applicant]
Qin et al., “Basnet: Boundary-aware salient object detection,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jun. 2019, pp. 7479-7489.
[cited by applicant]
Ronneberger et al., “U-net: Convolutional networks for biomedical image segmentation,” Presented at 18th International Conference, Munich, Germany, Oct. 5-9, 2015, pp. 234-241.
[cited by applicant]
Sengupta et al., “Background matting: The world is your green screen,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun. 2020, pp. 2291-2300.
[cited by applicant]
Shen et al., “Deep automatic portrait matting,” Presented at 14th European Conference, Amsterdam, The Netherlands, Oct. 11-14, 2016, pp. 92-107.
[cited by applicant]
Simonyan et al., “Very deep convolutional networks for large-scale image recognition.” arXiv, Dec. 23, 2014, 13 pages.
[cited by applicant]
Song et al., “Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection,” Proceedings of the European conference on computer vision (ECCV), Sep. 2018, 17 pages.
[cited by applicant]
Valipour et al., “Recurrent fully convolutional networks for video segmentation,” Presented at 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), Santa Rosa, CA, USA, Mar. 24-31, 2017, pp. 29-36.
[cited by applicant]
Wang et al., “Detect globally, refine locally: A novel approach to saliency detection,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jun. 2018, pp. 3127-3135.
[cited by applicant]
Xu et al. “Deep image matting,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jul. 2017, pp. 2970-2979.
[cited by applicant]
Zhang et al. “Amulet: Aggregating multi-level convolutional features for salient object detection,” Proceedings of the IEEE International Conference on Computer Vision, Oct. 2017, pp. 202-211.
[cited by applicant]
Zhang et al., “A late fusion con for digital matting,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jun. 2019, pp. 7469-7478.
[cited by applicant]
Zhang et al., “A novel graph-based optimization framework for salient object detection,” Pattern Recognition, Oct. 22, 2016, 35 pages.
[cited by applicant]
Zhao et al., “Pyramid scene parsing network,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jul. 2017, pp. 2881-2890.
[cited by applicant]
Lopez-Tapia, Santiago. “Gated Recurrent Networks for Video Super Resolution”, EUPISCO 2020. 700-704. (Year:2020).
[cited by applicant]
Wenzhe Shi et al. “Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network.” 2016 IEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. 1874-18…
[cited by applicant]