Anastasis Stathopoulos
anas.stathop@gmail.com


I am a researcher at Meta AI, based in New York City. I received my PhD in Computer Science from Rutgers University, where I was advised by Dimitris Metaxas. Before that, I graduated with a diploma (BS + MEng) in Electical & Computer Engineering (ECE) from the National Technical University of Athens. I have spent the summers of 2020 and 2021 at Amazon Prime Video working on methods for video understanding applications.

My research is in computer vision, with a particular interest in 3D human motion reconstruction and generation.


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News


Selected Publications

Score-Guided Diffusion for 3D Human Recovery
Anastasis Stathopoulos, Ligong Han, Dimitris Metaxas
Computer Vision and Pattern Recognition (CVPR), 2024
[project page] [code] [arxiv] [bibtex]

Solving inverse problems for 3D human pose and shape reconstruction with score guidance in the latent space of a diffusion model.

Learning Articulated Shape with Keypoint Pseudo-labels from Web Images
Anastasis Stathopoulos, Georgios Pavlakos, Ligong Han, Dimitris Metaxas
Computer Vision and Pattern Recognition (CVPR), 2023
[project page] [code & data] [arxiv] [bibtex]

Training models for 3D animal recovery with minimal annotations using large-scale collections of web images.

Exploiting Unlabeled Data with Vision and Language Models for Object Detection
Shiyu Zhao, Zhixing Zhang, Samuel Shulter, Long Zhao, Vijay Kumar, Anastasis Stathopoulos, Manmonahan Chandraker, Dimitris Metaxas
European Conference on Computer Vision (ECCV), 2022
[code & data] [arxiv] [bibtex]

Improving open-vocabulary and semi-supervised object detection with pseudo-labels from VLMs.

Dual Projection Generative Adversarial Networks for Conditional Image Generation
Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos, Yu Tian , Ruijiang Gao, Asim Kadav, Dimitris Metaxas
International Conference on Computer Vision (ICCV), 2021
[code] [arxiv] [bibtex]

Improving class separability and sample quality by balancing data and label matching in cGANs.



Credits to Jon Barron and Georgia Gkioxari