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Home/Authors/Igor Gilitschenski

Igor Gilitschenski

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 10:11 PM AMS

22

papers

731

total citations

papers (22)

SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting With Neural Radiance Fields

Housekeep: Tidying Virtual Households Using Commonsense Reasoning

SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models

NEURIPS 2023arXiv

SparsePose: Sparse-View Camera Pose Regression and Refinement

Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies

NEURIPS 2021arXiv

Reference-guided Controllable Inpainting of Neural Radiance Fields

LaTeRF: Label and Text Driven Object Radiance Fields

SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation

Producing and Leveraging Online Map Uncertainty in Trajectory Prediction

LEOD: Label-Efficient Object Detection for Event Cameras

trajdata: A Unified Interface to Multiple Human Trajectory Datasets

NEURIPS 2023arXiv

Mind the Time: Temporally-Controlled Multi-Event Video Generation

Pippo: High-Resolution Multi-View Humans from a Single Image

DenseDPO: Fine-Grained Temporal Preference Optimization for Video Diffusion Models

NEURIPS 2025arXiv

EventSplat: 3D Gaussian Splatting from Moving Event Cameras for Real-time Rendering

CTRL-D: Controllable Dynamic 3D Scene Editing with Personalized 2D Diffusion

LuxDiT: Lighting Estimation with Video Diffusion Transformer

NEURIPS 2025arXiv

Invertible Neural Skinning

SPAD: Spatially Aware Multi-View Diffusers

TESPEC: Temporally-Enhanced Self-Supervised Pretraining for Event Cameras

Track, Inpaint, Resplat: Subject-driven 3D and 4D Generation with Progressive Texture Infilling

NEURIPS 2025arXiv

Calibrated Value-Aware Model Learning with Probabilistic Environment Models