Artificial Intelligence & Machine Learning

Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are powering Adobe’s products and businesses. At Adobe, we use AI, ML, and DL to solve problems in content understanding (including images, videos, documents, audio, and more); recommendations and personalization; search and information retrieval; prediction and journey analysis; content segmentation, organization, editing, and generation; and more. 

Adobe Research scientists and engineers are developing the next generation of AI, ML, and DL-driven tools and features, inventing a future where Adobe enables new forms of creativity, and frees people from routine tasks, and allows enterprises to understand and act quickly on customer and business insights. Our team also leverages new approaches such as GANs (generative adversarial networks).    

Meet some of our researchersView More

Zeyu Jin

Senior Research Scientist

Iftikhar Ahamath Burhanuddin

Senior Research Scientist

Joon-Young Lee

Senior Research Scientist II

View our latest publicationsView More

Boosting Camera Motion Control for Video Diffusion Transformers

Cheong, S., Ceylan, D., Mustafa, A., Gilbert, A., Huang, C. (Nov. 24, 2025)

The British Machine Vision Conference (BMVC 2025)

Towards 3D-Consistent Video Generators

Huang, C., Mitra, N., Jeong, H., Yoon, J., Ceylan, D. (Nov. 24, 2025)

The British Machine Vision Conference (BMVC 2025)

A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality

Elmoghany, M., Rossi, R., Yoon, D., Mukherjee, S., Bakr, E., Mathur, P., Wu, G., Lai, V., Lipka, N., Zhang, R., Manjunatha, V., Nguyen, C., Dangi, D., Salinas, A., Taesiri, M., Chen, H., Huang, X., Barrow, J., Ahmed, N., Eldardiry, H., Park, N., Wang, Y., Cho, J., Nguyen, A., Tu, Z., Nguyen, T., Manocha, D., Elhoseiny, M., Dernoncourt, F. (Oct. 20, 2025)

ICCV 2025 LongVid Foundations Workshop

Project Know How

Project Know How allows users to track the origins of images and videos, even if they’ve been printed and captured from physical objects. Adobe’s implementation of Content Credentials is durable because of a combination of secure metadata, invisible watermarking, and fingerprinting technology. This project is an example of how Adobe aims to build trust by transparently showing the content’s origin, whether digital or physical.

View our latest newsView All News

Join us!

We are looking for researchers, engineers, and interns to take our technologies to the next level. We're recruiting, and we would love to hear from you!