Eddy Ilg

University of Technology Nuremberg

Computer Science · Physical Sciences

19h-index10.2kcitations61works3.52yr avg
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Research Topics

Advanced Vision and Imaging(30), Computer Graphics and Visualization Techniques(13), 3D Shape Modeling and Analysis(13), Advanced Image Processing Techniques(13), Advanced Neural Network Applications(11)

Publications61 total

CLIP is All You Need for Human-like Semantic Representations in Stable Diffusion
arXiv (Cornell University)·2025Open Access
3DFroMLLM: 3D Prototype Generation only from Pretrained Multimodal LLMs
arXiv (Cornell University)·2025Open Access
Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes
arXiv (Cornell University)·2025Open Access
EvOcc: Accurate Semantic Occupancy for Automated Driving Using Evidence Theory
2025
Imaging for All-Day Wearable Smart Glasses
arXiv (Cornell University)·2025Open Access
E-3DGS: Event-Based Novel View Rendering of Large-Scale Scenes Using 3D Gaussian Splatting
2025
Spurfies: Sparse-View Surface Reconstruction Using Local Geometry Priors
2025
E-3DGS: Event-Based Novel View Rendering of Large-Scale Scenes Using 3D Gaussian Splatting
arXiv (Cornell University)·2025· 1 citedOpen Access
SLayR: Scene Layout Generation with Rectified Flow
arXiv (Cornell University)·2024Open Access
LatentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction
Lecture notes in computer science·2024· 26 cited
Spurfies: Sparse Surface Reconstruction using Local Geometry Priors
arXiv (Cornell University)·2024Open Access
iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning
arXiv (Cornell University)·2024Open Access
Unsupervised Learning of Category-Level 3D Pose from Object-Centric Videos
arXiv (Cornell University)·2024Open Access
Neural Point Cloud Diffusion for Disentangled 3D Shape and Appearance Generation
2024· 4 cited
Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction
2024· 20 cited
Unsupervised Learning of Category-Level 3D Pose from Object-Centric Videos
2024
Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory
2024· 3 cited
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
arXiv (Cornell University)·2024Open Access
Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory
arXiv (Cornell University)·2024Open Access
Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes
Computer Graphics Forum·2024· 24 citedOpen Access
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Frequent Co-authors

Thomas Brox(20), Jan Eric Lenssen(13), Christopher Wewer(8), Bernt Schiele(7), Alexey Dosovitskiy(6), Osama Makansi(6), Raza Yunus(6), Tonmoy Saikia(5), Margret Keuper(5), Vladislav Golyanik(5), N. Michael Mayer(4), Özgün Çiçek(4), Anna Khoreva(4), Rodrigo Benenson(4), Kevin Raj(4), Richard Newcombe(4), Artur Jesslen(4), Adam Kortylewski(4), Philipp Fischer(3), Caner Hazırbaş(3)