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Tom Fischer

Hi – I am a second year PhD candidate in Computer Vision at the University of Technology Nuremberg, working with Prof. Eddy Ilg. My research focuses on building robust visual representations for 2D and 3D perception. I’m especially interested in object representation learning for pose estimation, where I’ve worked on category-level 9D pose estimation and frameworks that detect and infer poses directly from RGB images. More recently, I’ve been exploring self-supervised methods that reduce the need for manual annotations, with the goal of making perception systems more scalable and generalizable.

Outside of research, I enjoy cooking and experimenting with different cuisines (and of course eating them, too). I also like to travel, play tennis, go bouldering, and spend time with friends.

News

Feb 01, 2025 Our paper “Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes” has been accepted to ICCV 2025! 🚀
Sep 15, 2024 Our paper “iNeMo: Incremental neural mesh models for robust class-incremental learning” has been accepted to ECCV 2024! 🎯
Jul 01, 2024 Our paper “Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields” has been accepted to ICML 2024! 🎉

Selected Publications

  1. ICCV
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    Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes
    Tom Fischer, Xiaojie Zhang, and Eddy Ilg
    arXiv preprint arXiv:2508.02157, 2025
  2. ECCV
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    inemo: Incremental neural mesh models for robust class-incremental learning
    Tom Fischer, Yaoyao Liu, Artur Jesslen, and 6 more authors
    In European conference on computer vision, 2024