Brian Price
Principal Scientist
Adobe Research
Email:
As a research scientist at Adobe, I research Computer Vision, develop new technologies, transfer them to Adobe products, and work with universities and PhD students through collaborations and internships. (See full bio here)
Research Interests: Computer Vision, Graphics, and Machine Learning, especially segmentation (interactive object selection, matting, panoptic/semantic segmentation, video segmentation), image synthesis, and document understanding.
Latest News
CVPR 2025
Jun 13, 2025
I have one paper at CVPR this year plus two at CVPR workshops. Check them out at the Papers page.
ICLR 2025
Apr 23, 2025
Though I'm not at ICLR, I have a paper there: Refine-by-Align. Check it out at the conference or on my Papers page.
NeurIPS 2024
Dec 10, 2024
I'm here at NeurIPS for the first time. I'm be presenting my paper "Uncertainty-aware Fine-tuning of Segmentation Foundation Models."
Recent Publications
CompleteMe: Reference-based Human Image Completion
Yu-Ju Tsai, Brian Price, Qing Liu, Luis Figueroa, Daniil Pakhomov, Zhihong Ding, Scott Cohen, Ming-Hsuan Yang
ICCV 2025
[PDF] [Project page]
conSAMme: Achieving Consistent Segmentations with SAM
Josh Myers-Dean, Kangning Liu, Brian Price, Yifei Fan, and Danna Gurari
CVPR 2025 workshop - NTIRE
[PDF]
Recent Patents
Subobject Segmentation
Brian Price, Tai-yu Pan, Qing Liu
US Patent 12,462,388. Nov 4, 2025.
Performing Multiple Segmentation Tasks.
Sukjun Hwang, Jason Kuen, Brian Price, Zhe Lin, Jianming Zhang
US Patent 12,450,747. Oct 21, 2025.
Preparation systems for efficiently generating alpha mattes and modified digital videos utilizing polarized light.
Tenell Rhodes, Brian Price, Kenji Enomoto, Kevin Wampler.
US Patent 12,387,410. Aug 12, 2025.
Technologies Highlights
Object-aware Refine Edge
A few years back I helped to advise on the creation of the Select and Mask workspace in Photoshop that allows users to select objects in images. Photoshop added a new mode that allows for improved extraction of hair for complex images. This mode is a follow on to our Deep Image Matting paper from CVPR 2017.