Svetlana Lazebnik

20012019
If you made any changes in Pure, your changes will be visible here soon.

Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 2 Similar Profiles
Labels Engineering & Materials Science
Binary codes Engineering & Materials Science
Textures Engineering & Materials Science
Image retrieval Engineering & Materials Science
Internet Engineering & Materials Science
Semantics Engineering & Materials Science
Object recognition Engineering & Materials Science
Experiments Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2001 2019

Combining Multiple Cues for Visual Madlibs Question Answering

Tommasi, T., Mallya, A., Plummer, B., Lazebnik, S., Berg, A. C. & Berg, T. L., Jan 15 2019, In : International Journal of Computer Vision. 127, 1, p. 38-60 23 p.

Research output: Contribution to journalArticle

Feature extraction

Learning Two-Branch Neural Networks for Image-Text Matching Tasks

Wang, L., Li, Y., Huang, J. & Lazebnik, S., Feb 1 2019, In : IEEE transactions on pattern analysis and machine intelligence. 41, 2, p. 394-407 14 p., 8268651.

Research output: Contribution to journalArticle

Branch
Neural Networks
Sampling
Neural networks
Network Structure

Conditional image-text embedding networks

Plummer, B. A., Kordas, P., Kiapour, M. H., Zheng, S., Piramuthu, R. & Lazebnik, S., Jan 1 2018, Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. Hebert, M., Ferrari, V., Sminchisescu, C. & Weiss, Y. (eds.). Springer-Verlag, p. 258-274 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11216 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Electric grounding
Differentiate
Assign
Baseline
Simplify

Out of the box: Reasoning with graph convolution nets for factual visual question answering

Narasimhan, M., Lazebnik, S. & Schwing, A. G., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 2654-2665 12 p.

Research output: Contribution to journalConference article

Convolution

PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

Mallya, A. & Lazebnik, S., Dec 14 2018, Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018. IEEE Computer Society, p. 7765-7773 9 p. 8578908. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Network architecture
Redundancy
Experiments
Deep neural networks