Publications

Our papers and articles

25 publications, auto-synced daily from OpenAlex.

  • Matryoshka Gaussian Splatting

    Z Guo, B Zhang, H Aktas, K Fogarty, J Hu, NK Aslan, W Li, C Baykal, ...

    arXiv preprint arXiv:2603.19234 Preprint

    Project

  • PoseCraft: Tokenized 3D Body Landmark and Camera Conditioning for Photorealistic Human Image Synthesis

    Z Guo, J Yang, K Fogarty, J Wan, B Zhang, T Wu, W Xia, C Zhou, ...

    arXiv preprint arXiv:2602.19350 Preprint

    Project

  • Learning-guided Kansa collocation for forward and inverse PDEs beyond linearity

    Z Hu, W Chen, C Öztireli, C Zhou, F Zhong

    arXiv preprint arXiv:2602.07970 Preprint

    Project

  • Quartet of Diffusions: Structure-Aware Point Cloud Generation through Part and Symmetry Guidance

    C Zhou, F Zhong, W Xia, A Miao, C Baykal, C Oztireli

    arXiv preprint arXiv:2601.20425 Preprint

    Project

  • Chord: Generation of collision-free, house-scale, and organized digital twins for 3d indoor scenes with controllable floor plans and optimal layouts

    C Su, Y Fu, Z Hu, J Yang, P Hanji, S Wang, X Zhao, C Öztireli, F Zhong

    arXiv preprint arXiv:2503.11958 Preprint

    Project

  • Restereo: Diffusion stereo video generation and restoration

    X Huang, AK Singh, F Dubost, CN Vasconcelos, S Khattar, L Shi, ...

    arXiv preprint arXiv:2506.06023 Preprint

    Project

  • Features Emerge as Discrete States: The First Application of SAEs to 3D Representations

    A Miao, C Zhou, J Zhou, C Oztireli

    arXiv preprint arXiv:2512.11263 Preprint

    Project

  • Twist and Compute: The Cost of Pose in 3D Generative Diffusion

    K Fogarty, J Foster, B Zhang, J Yang, C Öztireli

    arXiv preprint arXiv:2511.08203 Preprint

    Project

  • Self-Supervised Implicit Attention Priors for Point Cloud Reconstruction

    K Fogarty, C Cai, J Yang, Z Guo, C Öztireli

    arXiv preprint arXiv:2511.04864 Preprint

    Project

  • FreNBRDF: A Frequency-Rectified Neural Material Representation

    C Zhou, Z Hu, C Oztireli

    arXiv preprint arXiv:2507.00476 Preprint

    Project

  • Feed-forward bullet-time reconstruction of dynamic scenes from monocular videos

    H Liang, J Ren, A Mirzaei, A Torralba, Z Liu, I Gilitschenski, S Fidler, ...

    arXiv preprint arXiv:2412.03526 Preprint

    Project

  • Zero-shot machine unlearning at scale via lipschitz regularization

    J Foster, K Fogarty, S Schoepf, C Öztireli, A Brintrup

    arXiv preprint arXiv:2402.01401 3 (8) Preprint

    Project

  • An information theoretic approach to machine unlearning

    J Foster, K Fogarty, S Schoepf, Z Dugue, C Öztireli, A Brintrup

    arXiv preprint arXiv:2402.01401 Preprint

    Project

  • Physically based neural bidirectional reflectance distribution function

    C Zhou, A Sztrajman, G Rainer, F Zhong, F Gokbudak, Z Guo, W Xia, ...

    arXiv preprint arXiv:2411.02347 Preprint

    Project

  • SYM3D: learning symmetric triplanes for better 3D-awareness of GANs

    J Yang, K Fogarty, F Zhong, C Oztireli

    arXiv preprint arXiv:2406.06432 Preprint

    Project

  • Neumadiff: Neural material synthesis via hyperdiffusion

    C Zhou, Z Hu, A Sztrajman, Y Cai, Y Liu, C Oztireli

    arXiv preprint arXiv:2411.12015 Preprint

    Project

  • Evolutive Rendering Models

    F Zhan, H Liang, Y Wang, M Niemeyer, M Oechsle, A Kortylewski, ...

    arXiv preprint arXiv:2405.17531 Preprint

    Project

  • Neural fields with hard constraints of arbitrary differential order

    F Zhong, K Fogarty, P Hanji, T Wu, A Sztrajman, A Spielberg, ...

    arXiv preprint arXiv:2306.08943 Preprint

    Project

  • Hypernetworks for generalizable BRDF estimation

    F Gokbudak, A Sztrajman, C Zhou, F Zhong, R Mantiuk, C Öztireli

    arXiv preprint ArXiv:2311.15783 Preprint

    Project

  • Statistical shape representations for temporal registration of plant components in 3D

    K Heiwolt, C Öztireli, G Cielniak

    arXiv preprint arXiv:2209.11526 Preprint

    Project

  • Shapley value as principled metric for structured network pruning

    M Ancona, C Öztireli, M Gross

    arXiv preprint arXiv:2006.01795 Preprint

    Project

  • Towards better understanding of gradient-based attribution methods for Deep Neural Networks. doi: 10.48550

    M Ancona, E Ceolini, C Öztireli, M Gross

    arXiv preprint arXiv.1711.06104 Preprint

    Project

  • Towards better understanding of gradient-based attribution methods for deep neural networks

    M Ancona, E Ceolini, C Öztireli, M Gross

    arXiv preprint arXiv:1711.06104 Preprint

    Project

  • Towards better understanding of gradient-based attribution methods for deep neural networksarXiv preprint

    M Ancona, E Ceolini, C Öztireli

    arXiv preprint arXiv:1711.06104 2 Preprint

    Project

  • Ceolini Enea, Öztireli Cengiz, and Gross Markus. 2017. Towards better understanding of gradient-based attribution methods for deep neural networks

    A Marco

    arXiv preprint arXiv:1711.06104 Preprint

    Project