Yawar Siddiqui

prof_pic.jpg

yawarnihal[at]gmail[dot]com

Hi! I’m Yawar, presently an AI Research Scientist (intern) at GenAI, Meta in London. I did my PhD at the Visual Computing and Artificial Intelligence group of Prof. Matthias Niessner at the Technical University of Munich, Germany. My work focuses on 3D reconstruction, scene understanding and 3D generative models.

Before the PhD, I did a Masters in Informatics at TUM, Germany, and my Bachelors in Computer Science at Jamia Millia Islamia, New Delhi, India, graduating with high distinction and at the top of the class respectively.

In the past, I have worked with Adobe Systems in India as a software engineer. During my time at TUM, I’ve had the pleasure of interning with Thabo Beeler and Derek Bradley at Disney Research in Zurich, and with Peter Konschieder at Meta Reality Labs, also in Zurich.


Research

  1. meshgpt.gif
    CVPR24
    MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers
    Yawar Siddiqui, Antonio Alliegro, Alexey Artemov, Tatiana Tommasi, Daniele Sirigatti, Vladislav Rosov, Angela Dai, and Matthias Nießner
    In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2024
    Project PDF Video
  2. polydiff.gif
    ARXIV23
    PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models
    Antonio Alliegro, Yawar Siddiqui, Tatiana Tommasi, and Matthias Nießner
    arXiv preprint arXiv:2312.11417, 2023
    PDF Video
  3. text2tex.gif
    ICCV23
    Text2Tex: Text-driven Texture Synthesis via Diffusion Models
    Dave Zhenyu Chen, Yawar Siddiqui, Hsin-Ying Lee, Sergey Tulyakov, and Matthias Nießner
    In Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
    Project PDF Video Code
  4. panopli.gif
    CVPR23
    Panoptic Lifting for 3D Scene Understanding with Neural Fields
    Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Buló, Norman Müller, Matthias Nießner, Angela Dai, and Peter Kontschieder
    In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2023
    Project PDF Video Code
  5. diffrf.gif
    CVPR23
    DiffRF: Rendering-Guided 3D Radiance Field Diffusion
    Norman Müller, Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, and Matthias Nießner
    In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2023
    Project PDF Video
  6. texturify.gif
    ECCV22
    Texturify: Generating textures on 3d shape surfaces
    Yawar Siddiqui, Justus Thies, Fangchang Ma, Qi Shan, Matthias Nießner, and Angela Dai
    In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part III, 2022
    Project PDF Video Code
  7. retrievalfuse.gif
    ICCV21
    Retrievalfuse: Neural 3d scene reconstruction with a database
    Yawar Siddiqui, Justus Thies, Fangchang Ma, Qi Shan, Matthias Nießner, and Angela Dai
    In Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021
    Project PDF Video Code
  8. spsg.gif
    CVPR21
    Spsg: Self-supervised photometric scene generation from rgb-d scans
    Angela Dai, Yawar Siddiqui, Justus Thies, Julien Valentin, and Matthias Nießner
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021
    Project PDF Video Code
  9. viewal.gif
    CVPR20
    Viewal: Active learning with viewpoint entropy for semantic segmentation
    Yawar Siddiqui, Julien Valentin, and Matthias Nießner
    In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2020
    Project PDF Video Code
  10. clustering.gif
    ARXIV18
    Clustering with deep learning: Taxonomy and new methods
    Elie Aljalbout, Vladimir Golkov, Yawar Siddiqui, Maximilian Strobel, and Daniel Cremers
    arXiv preprint arXiv:1801.07648, 2018
    PDF Code

Teaching


Seminar on Neural Radiance Fields

Course Coordinator, Winter 2022/23, Summer 2023

Machine Learning for 3D Geometry

Teaching Assistant, Summer 2021

Advanced Deep Learning for Computer Vision

Teaching Assistant, Winter 2020/21

Introduction to Deep Learning

Teaching Assistant, Winter 2019/20

Reviewer Experience

Reviewed in the past for CVPR, ICCV, ECCV.