World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
5380
World Ranking
12576
National Ranking
5098

Overview

Anelia Angelova is affiliated with Google in the United States and has a research portfolio concentrated in the field of Computer Science, with a substantial focus on Computer Vision and Pattern Recognition. Their work falls within several key subfields, including Artificial Intelligence, Aerospace Engineering, Geology, and Computational Mechanics.

The scientist's research topics include multimodal machine learning applications, domain adaptation and few-shot learning, human pose and action recognition, advanced image and video retrieval techniques, advanced neural network applications, robotics and sensor-based localization, as well as 3D surveying and cultural heritage.

Anelia Angelova's publication record includes over 124 works primarily situated in the intersections of Computer Science and its sub-disciplines. The frequent publication venues for their work consist of:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Lecture Notes in Computer Science
  • IEEE Robotics and Automation Letters
  • Applied AI Letters

Highlighted recent papers illustrate a focus on vision and language models, object detection, and depth learning in dynamic scenes. These include:

  • PaLI: A Jointly-Scaled Multilingual Language-Image Model (2022), published in arXiv (Cornell University)
  • Learning Open-World Object Proposals Without Learning to Classify (2022), IEEE Robotics and Automation Letters
  • Unsupervised Monocular Depth Learning in Dynamic Scenes (2020), arXiv (Cornell University)
  • PaLI-X: On Scaling up a Multilingual Vision and Language Model (2023), arXiv (Cornell University)
  • F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models (2022), arXiv (Cornell University)

Collaboration has been an important aspect of their research, with frequent co-authors including AJ Piergiovanni, Weicheng Kuo, Michael S. Ryoo, Dahun Kim, and Tsung-Yi Lin. These collaborations span diverse areas within computer vision and machine learning.

Best Publications

  • Real-time grasp detection using convolutional neural networks

    Joseph Redmon;Anelia Angelova

  • Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

    Reza Mahjourian;Martin Wicke;Anelia Angelova

  • PaLI: A Jointly-Scaled Multilingual Language-Image Model

    Unknown

  • Depth Prediction without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos

    Vincent Michael Casser;Soeren Pirk;Reza Mahjourian;Anelia Angelova

  • Depth From Videos in the Wild: Unsupervised Monocular Depth Learning From Unknown Cameras

    Ariel Gordon;Hanhan Li;Rico Jonschkowski;Anelia Angelova

  • Real-Time Pedestrian Detection With Deep Network Cascades

    Anelia Angelova;Alex Krizhevsky;Vincent Vanhoucke;Abhijit S. Ogale

  • Computer Vision on Mars

    Larry Matthies;Mark Maimone;Andrew Johnson;Yang Cheng

  • Efficient Object Detection and Segmentation for Fine-Grained Recognition

    Anelia Angelova;Shenghuo Zhu

  • Learning and prediction of slip from visual information

    Anelia Angelova;Larry H. Matthies;Daniel M. Helmick;Pietro Perona

  • Pruning training sets for learning of object categories

    A. Angelova;Y. Abu-Mostafam;P. Perona

  • What Matters in Unsupervised Optical Flow

    Rico Jonschkowski;Austin Stone;Jonathan T. Barron;Ariel Gordon

  • Evolving Losses for Unsupervised Video Representation Learning

    AJ Piergiovanni;Anelia Angelova;Michael S. Ryoo

  • ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors

    Weicheng Kuo;Anelia Angelova;Jitendra Malik;Tsung-Yi Lin

  • Pedestrian detection with a Large-Field-Of-View deep network

    Anelia Angelova;Alex Krizhevsky;Vincent Vanhoucke

  • KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects

    Xingyu Liu;Rico Jonschkowski;Anelia Angelova;Kurt Konolige

  • Terrain Adaptive Navigation for planetary rovers

    Daniel Helmick;Anelia Angelova;Larry Matthies

  • Fast Terrain Classification Using Variable-Length Representation for Autonomous Navigation

    A. Angelova;L. Matthies;D. Helmick;P. Perona

  • Probabilistic Object Detection: Definition and Evaluation

    David Hall;Feras Dayoub;John Skinner;Haoyang Zhang

  • Learning Open-World Object Proposals without Learning to Classify

    Dahun Kim;Tsung-Yi Lin;Anelia Angelova;In So Kweon

  • Learning to predict slip for ground robots

    A. Angelova;L. Matthies;D. Helmick;G. Sibley

  • PaLI-X: On Scaling up a Multilingual Vision and Language Model

    Unknown

  • Towards learned traversability for robot navigation: From underfoot to the far field

    Andrew Howard;Michael J. Turmon;Larry H. Matthies;Benyang Tang

  • Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

    Reza Mahjourian;Martin Wicke;Anelia Angelova

  • Improved generator objectives for GANs

    Ben Poole;Alexander A. Alemi;Jascha Sohl-Dickstein;Anelia Angelova

  • Slip prediction using visual information

    Anelia Angelova;Larry H. Matthies;Daniel M. Helmick;Pietro Perona

  • Image segmentation for large-scale subcategory flower recognition

    A. Angelova;Shenghuo Zhu;Yuanqing Lin

  • TokenLearner: Adaptive Space-Time Tokenization for Videos

    Michael Ryoo;AJ Piergiovanni;Anurag Arnab;Mostafa Dehghani

  • Learning and prediction of slip from visual information: Research Articles

    Anelia Angelova;Larry Matthies;Daniel Helmick;Pietro Perona

Frequent Co-Authors

Michael S. Ryoo
Michael S. Ryoo Stony Brook University
Larry Matthies
Larry Matthies Jet Propulsion Lab
Tsung-Yi Lin
Tsung-Yi Lin Nvidia (United States)
Pietro Perona
Pietro Perona California Institute of Technology
Alexander Toshev
Alexander Toshev Apple (United States)
Vincent Vanhoucke
Vincent Vanhoucke Google (United States)
Irfan Essa
Irfan Essa Georgia Institute of Technology
Kurt Konolige
Kurt Konolige Google (United States)
Angela Dai
Angela Dai Technical University of Munich
Andrew W. Howard
Andrew W. Howard California Institute of Technology

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