World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
38134
World Ranking
3719
National Ranking
1774

Research.com Recognitions

  • 2021 - IEEE Fellow For contributions to computer vision
  • 2013 - Fellow of Alfred P. Sloan Foundation

Overview

Svetlana Lazebnik is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research centers on the field of Computer Science, with a primary focus on Computer Vision and Pattern Recognition. Subfields of study include Artificial Intelligence, Computational Mechanics, Social Psychology, and Control and Systems Engineering.

The scientist's research covers a variety of topics, including:

  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Generative Adversarial Networks and Image Synthesis
  • Human Pose and Action Recognition
  • Reinforcement Learning in Robotics
  • Domain Adaptation and Few-Shot Learning
  • 3D Shape Modeling and Analysis

Recent notable papers include:

  • "Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models," 2024, arXiv (Cornell University)
  • "Revisiting Image-Language Networks for Open-Ended Phrase Detection," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Memory-Efficient Incremental Learning Through Feature Adaptation," 2020, Lecture notes in computer science

Their frequent co-authors include:

  • Unnat Jain
  • Alexander G. Schwing
  • Viraj Shah
  • Aiyu Cui
  • Daniel McKee

Common publication venues are:

  • arXiv (Cornell University)
  • UNC Libraries
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Lecture notes in computer science

Svetlana Lazebnik has been recognized as a Fellow of the Alfred P. Sloan Foundation in 2013. In 2021, they were named an IEEE Fellow for contributions to computer vision.

Best Publications

  • Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

    S. Lazebnik;C. Schmid;J. Ponce

  • Iterative Quantization: A Procrustean Approach to Learning Binary Codes for Large-Scale Image Retrieval

    Yunchao Gong;Svetlana Lazebnik;Albert Gordo;Florent Perronnin

  • Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study

    Jianguo Zhang;M. Marszalek;S. Lazebnik;C. Schmid

  • A sparse texture representation using local affine regions

    S. Lazebnik;C. Schmid;J. Ponce

  • Iterative quantization: A procrustean approach to learning binary codes

    Yunchao Gong;Svetlana Lazebnik

  • Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

    Bryan A. Plummer;Liwei Wang;Chris M. Cervantes;Juan C. Caicedo

  • Multi-scale Orderless Pooling of Deep Convolutional Activation Features

    Yunchao Gong;Liwei Wang;Ruiqi Guo;Svetlana Lazebnik

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

    Arun Mallya;Svetlana Lazebnik

  • Superparsing: Scalable Nonparametric Image Parsing with Superpixels

    Joseph Tighe;Svetlana Lazebnik

  • Learning Deep Structure-Preserving Image-Text Embeddings

    Liwei Wang;Yin Li;Svetlana Lazebnik

  • Locality-sensitive binary codes from shift-invariant kernels

    Maxim Raginsky;Svetlana Lazebnik

  • Building Rome on a cloudless day

    Jan-Michael Frahm;Pierre Fite-Georgel;David Gallup;Tim Johnson

  • Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

    Arun Mallya;Dillon Davis;Svetlana Lazebnik

  • A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics

    Yunchao Gong;Qifa Ke;Michael Isard;Svetlana Lazebnik

  • 3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints

    Fred Rothganger;Svetlana Lazebnik;Cordelia Schmid;Jean Ponce

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

    Liwei Wang;Yin Li;Jing Huang;Svetlana Lazebnik

  • Scene recognition and weakly supervised object localization with deformable part-based models

    Megha Pandey;Svetlana Lazebnik

  • Active Object Localization with Deep Reinforcement Learning

    Juan C. Caicedo;Svetlana Lazebnik

  • Where to Buy It: Matching Street Clothing Photos in Online Shops

    M. Hadi Kiapour;Xufeng Han;Svetlana Lazebnik;Alexander C. Berg

  • Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs

    Xiaowei Li;Changchang Wu;Christopher Zach;Svetlana Lazebnik

  • Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

    Bryan A. Plummer;Liwei Wang;Chris M. Cervantes;Juan C. Caicedo

  • Local Features and Kernels for Classication of Texture and Object Categories: A Comprehensive Study

    Jianguo Zhang;Svetlana Lazebnik;Cordelia Schmid

Frequent Co-Authors

Jean Ponce
Jean Ponce École Normale Supérieure
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Alexander G. Schwing
Alexander G. Schwing University of Illinois at Urbana-Champaign
Liwei Wang
Liwei Wang Peking University
Yoichi Sato
Yoichi Sato University of Tokyo
Pietro Perona
Pietro Perona California Institute of Technology
Ali Farhadi
Ali Farhadi University of Washington
Julia Hockenmaier
Julia Hockenmaier University of Illinois at Urbana-Champaign
Tamara L. Berg
Tamara L. Berg University of North Carolina at Chapel Hill

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