A robust computational test for overlap of two arbitrary-dimensional ellipsoids in fault-detection of Kalman filters. - Igor Gilitschenski; Uwe D. Hanebeck (FUSION, 2012)

Efficient deterministic dirac mixture approximation of Gaussian distributions. - Igor Gilitschenski; Uwe D. Hanebeck (ACC, 2013)

Recursive nonlinear filtering for angular data based on circular distributions. - Gerhard Kurz; Igor Gilitschenski; Uwe D. Hanebeck (ACC, 2013)

Bearings-only sensor scheduling using circular statistics. - Igor Gilitschenski; Gerhard Kurz; Uwe D. Hanebeck (FUSION, 2013)

Recursive estimation of orientation based on the Bingham distribution. - Gerhard Kurz; Igor Gilitschenski; Simon Julier; Uwe D. Hanebeck (FUSION, 2013)

Nonlinear measurement update for estimation of angular systems based on circular distributions. - Gerhard Kurz; Igor Gilitschenski; Uwe D. Hanebeck (ACC, 2014)

Bivariate angular estimation under consideration of dependencies using directional statistics. - Gerhard Kurz; Igor Gilitschenski; Maxim Dolgov; Uwe D. Hanebeck (CDC, 2014)

Estimation and Scheduling in Sensor-Networks Involving Periodic Data. - Igor Gilitschenski (Joint Workshop of the German Research Training Groups in Computer Science, 2014)

A new probability distribution for simultaneous representation of uncertain position and orientation. - Igor Gilitschenski; Gerhard Kurz; Simon J. Julier; Uwe D. Hanebeck (FUSION, 2014)

Deterministic Dirac mixture approximation of Gaussian mixtures. - Igor Gilitschenski; Jannik Steinbring; Uwe D. Hanebeck; Miroslav Simandl (FUSION, 2014)

Deterministic approximation of circular densities with symmetric Dirac mixtures based on two circular moments. - Gerhard Kurz; Igor Gilitschenski; Uwe D. Hanebeck (FUSION, 2014)

Efficient Bingham filtering based on saddlepoint approximations. - Igor Gilitschenski; Gerhard Kurz; Simon J. Julier; Uwe D. Hanebeck (MFI, 2014)

The partially wrapped normal distribution for SE(2) estimation. - Gerhard Kurz; Igor Gilitschenski; Uwe D. Hanebeck (MFI, 2014)

Exact and Approximate Hidden Markov Chain Filters Based on Discrete Observations. - Nicole Bäuerle; Igor Gilitschenski; Uwe D. Hanebeck (CoRR, 2014)

Efficient Evaluation of the Probability Density Function of a Wrapped Normal Distribution. - Gerhard Kurz; Igor Gilitschenski; Uwe D. Hanebeck (CoRR, 2014)

Non-identity measurement models for orientation estimation based on directional statistics. - Igor Gilitschenski; Gerhard Kurz; Uwe D. Hanebeck (FUSION, 2015)

A stochastic filter for planar rigid-body motions. - Igor Gilitschenski; Gerhard Kurz; Uwe D. Hanebeck (MFI, 2015)

Recursive Bayesian Filtering in Circular State Spaces. - Gerhard Kurz; Igor Gilitschenski; Uwe D. Hanebeck (CoRR, 2015)

Will It Last? Learning Stable Features for Long-Term Visual Localization. - Marcin Dymczyk; Elena Stumm; Juan I. Nieto 001; Roland Siegwart; Igor Gilitschenski (3DV, 2016)

Optimal quantization of circular distributions. - Igor Gilitschenski; Gerhard Kurz; Uwe D. Hanebeck; Roland Siegwart (FUSION, 2016)

Appearance-based landmark selection for efficient long-term visual localization. - Mathias Bürki; Igor Gilitschenski; Elena Stumm; Roland Siegwart; Juan I. Nieto 001 (IROS, 2016)

Generalized information filtering for MAV parameter estimation. - Michael Burri; Michael Bloesch; Dominik Schindler; Igor Gilitschenski; Zachary Taylor; Roland Siegwart (IROS, 2016)

Erasing bad memories: Agent-side summarization for long-term mapping. - Marcin Dymczyk; Thomas Schneider 007; Igor Gilitschenski; Roland Siegwart; Elena Stumm (IROS, 2016)

Robust map generation for fixed-wing UAVs with low-cost highly-oblique monocular cameras. - Timo Hinzmann; Thomas Schneider 007; Marcin Dymczyk; Amir Melzer; Thomas Mantel; Roland Siegwart; Igor Gilitschenski (IROS, 2016)

Collaborative 3D Reconstruction Using Heterogeneous UAVs: System and Experiments. - Timo Hinzmann; Thomas Stastny; Gianpaolo Conte; Patrick Doherty 001; Piotr Rudol; Mariusz Wzorek; Enric Galceran; Roland Siegwart; Igor Gilitschenski (ISER, 2016)

Monocular Visual-Inertial SLAM for Fixed-Wing UAVs Using Sliding Window Based Nonlinear Optimization. - Timo Hinzmann; Thomas Schneider 007; Marcin Dymczyk; Andreas Schaffner; Simon Lynen; Roland Siegwart; Igor Gilitschenski (ISVC (1), 2016)

A data-driven approach for pedestrian intention estimation. - Benjamin Völz; Karsten Behrendt; Holger Mielenz; Igor Gilitschenski; Roland Siegwart; Juan I. Nieto 001 (ITSC, 2016)

Gone with the Wind: Nonlinear Guidance for Small Fixed-Wing Aircrafts in Arbitrarily Strong Windfields. - Luca Furieri; Thomas Stastny; Lorenzo Marconi 001; Roland Siegwart; Igor Gilitschenski (CoRR, 2016)

Robust Estimation and Applications in Robotics. - Michael Bosse; Gabriel Agamennoni; Igor Gilitschenski (Found. Trends Robotics, 2016)

Unscented von Mises-Fisher Filtering. - Gerhard Kurz; Igor Gilitschenski; Uwe D. Hanebeck (IEEE Signal Process. Lett., 2016)

Unscented Orientation Estimation Based on the Bingham Distribution. - Igor Gilitschenski; Gerhard Kurz; Simon J. Julier; Uwe D. Hanebeck (IEEE Trans. Autom. Control., 2016)

Deterministic Sampling for Nonlinear Dynamic State Estimation. - Igor Gilitschenski (2016)

Gone with the wind: Nonlinear guidance for small fixed-wing aircraft in arbitrarily strong windfields. - Luca Furieri; Thomas Stastny; Lorenzo Marconi 001; Roland Siegwart; Igor Gilitschenski (ACC, 2017)

Evaluation of Combined Time-Offset Estimation and Hand-Eye Calibration on Robotic Datasets. - Fadri Furrer; Marius Fehr; Tonci Novkovic; Hannes Sommer; Igor Gilitschenski; Roland Siegwart (FSR, 2017)

TSDF-based change detection for consistent long-term dense reconstruction and dynamic object discovery. - Marius Fehr; Fadri Furrer; Ivan Dryanovski; Jürgen Sturm; Igor Gilitschenski; Roland Siegwart; Cesar Cadena 001 (ICRA, 2017)

Efficient descriptor learning for large scale localization. - Antonio Loquercio; Marcin Dymczyk; Bernhard Zeisl; Simon Lynen; Igor Gilitschenski; Roland Siegwart (ICRA, 2017)

Map quality evaluation for visual localization. - Hamza Merzic; Elena Stumm; Marcin Dymczyk; Roland Siegwart; Igor Gilitschenski (ICRA, 2017)

Visual-inertial self-calibration on informative motion segments. - Thomas Schneider 007; Mingyang Li; Michael Burri; Juan I. Nieto 001; Roland Siegwart; Igor Gilitschenski (ICRA, 2017)

A low-cost system for high-rate, high-accuracy temporal calibration for LIDARs and cameras. - Hannes Sommer; Raghav Khanna; Igor Gilitschenski; Zachary Taylor; Roland Siegwart; Juan I. Nieto 001 (IROS, 2017)

Onboard real-time dense reconstruction of large-scale environments for UAV. - Anurag Sai Vempati; Igor Gilitschenski; Juan I. Nieto 001; Paul A. Beardsley; Roland Siegwart (IROS, 2017)

Directional Statistics and Filtering Using libDirectional. - Gerhard Kurz; Igor Gilitschenski; Florian Pfaff; Lukas Drude; Uwe D. Hanebeck; Reinhold Haeb-Umbach; Roland Yves Siegwart (CoRR, 2017)

LandmarkBoost: Efficient visualContext Classifiers for Robust Localization. - Marcin Dymczyk; Igor Gilitschenski; Juan I. Nieto 001; Simon Lynen; Bernhard Zeisl; Roland Siegwart (IROS, 2018)

ShadowCam: Real-Time Detection of Moving Obstacles Behind A Corner For Autonomous Vehicles. - Felix Naser; Igor Gilitschenski; Guy Rosman; Alexander Amini; Frédo Durand; Antonio Torralba 001; Gregory W. Wornell; William T. Freeman; Sertac Karaman; Daniela Rus (ITSC, 2018)

Map Management for Efficient Long-Term Visual Localization in Outdoor Environments. - Mathias Bürki; Marcin Dymczyk; Igor Gilitschenski; Cesar Cadena 001; Roland Siegwart; Juan I. Nieto 001 (Intelligent Vehicles Symposium, 2018)

Sampling-Based Approximation Algorithms for Reachability Analysis with Provable Guarantees. - Lucas Liebenwein; Cenk Baykal; Igor Gilitschenski; Sertac Karaman; Daniela Rus (Robotics: Science and Systems, 2018)

Voliro: An Omnidirectional Hexacopter With Tiltable Rotors. - Mina Kamel; Sebastian Verling; Omar Elkhatib; Christian Sprecher; Paula Wulkop; Zachary Taylor; Roland Siegwart; Igor Gilitschenski (CoRR, 2018)

Why and How to Avoid the Flipped Quaternion Multiplication. - Hannes Sommer; Igor Gilitschenski; Michael Bloesch; Stephan Weiss 002; Roland Siegwart; Juan I. Nieto 001 (CoRR, 2018)

Learning 3D Segment Descriptors for Place Recognition. - Andrei Cramariuc; Renaud Dubé; Hannes Sommer; Roland Siegwart; Igor Gilitschenski (CoRR, 2018)

LandmarkBoost: Efficient Visual Context Classifiers for Robust Localization. - Marcin Dymczyk; Igor Gilitschenski; Juan I. Nieto 001; Simon Lynen; Bernhard Zeisl; Roland Siegwart (CoRR, 2018)

Incremental-Segment-Based Localization in 3-D Point Clouds. - Renaud Dubé; Mattia G. Gollub; Hannes Sommer; Igor Gilitschenski; Roland Siegwart; Cesar Cadena 001; Juan I. Nieto 001 (IEEE Robotics Autom. Lett., 2018)

Free LSD: Prior-Free Visual Landing Site Detection for Autonomous Planes. - Timo Hinzmann; Thomas Stastny; Cesar Cadena 001; Roland Siegwart; Igor Gilitschenski (IEEE Robotics Autom. Lett., 2018)

Maplab: An Open Framework for Research in Visual-Inertial Mapping and Localization. - Thomas Schneider 007; Marcin Dymczyk; Marius Fehr; Kevin Egger; Simon Lynen; Igor Gilitschenski; Roland Siegwart (IEEE Robotics Autom. Lett., 2018)

The Voliro Omniorientational Hexacopter: An Agile and Maneuverable Tiltable-Rotor Aerial Vehicle. - Mina Kamel; Sebastian Verling; Omar Elkhatib; Christian Sprecher; Paula Wulkop; Zachary Taylor; Roland Siegwart; Igor Gilitschenski (IEEE Robotics Autom. Mag., 2018)

Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds. - Cenk Baykal; Lucas Liebenwein; Igor Gilitschenski; Dan Feldman; Daniela Rus (ICLR (Poster), 2019)

Infrastructure-free NLoS Obstacle Detection for Autonomous Cars. - Felix Naser; Igor Gilitschenski; Alexander Amini; Christina Liao; Guy Rosman; Sertac Karaman; Daniela Rus (IROS, 2019)

Range-based Cooperative Localization with Nonlinear Observability Analysis. - Brandon Araki; Igor Gilitschenski; Tatum Ogata; Alex Wallar; Wilko Schwarting; Zareen Choudhury; Sertac Karaman; Daniela Rus (ITSC, 2019)

SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks. - Cenk Baykal; Lucas Liebenwein; Igor Gilitschenski; Dan Feldman; Daniela Rus (CoRR, 2019)

Deep Context Map: Agent Trajectory Prediction using Location-specific Latent Maps. - Igor Gilitschenski; Guy Rosman; Arjun Gupta; Sertac Karaman; Daniela Rus (CoRR, 2019)

Appearance-based landmark selection for visual localization. - Mathias Bürki; Cesar Cadena 001; Igor Gilitschenski; Roland Siegwart; Juan I. Nieto 001 (J. Field Robotics, 2019)

Probabilistic Risk Metrics for Navigating Occluded Intersections. - Stephen G. McGill; Guy Rosman; Teddy Ort; Alyssa Pierson; Igor Gilitschenski; Brandon Araki; Luke Fletcher; Sertac Karaman; Daniela Rus; John J. Leonard (IEEE Robotics Autom. Lett., 2019)

Inferring Pedestrian Motions at Urban Crosswalks. - Benjamin Völz; Holger Mielenz; Igor Gilitschenski; Roland Siegwart; Juan I. Nieto 001 (IEEE Trans. Intell. Transp. Syst., 2019)

Differentiable Logic Layer for Rule Guided Trajectory Prediction. - Xiao Li 025; Guy Rosman; Igor Gilitschenski; Jonathan A. DeCastro; Cristian Ioan Vasile; Sertac Karaman; Daniela Rus (CoRL, 2020)

Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space. - Wilko Schwarting; Tim Seyde; Igor Gilitschenski; Lucas Liebenwein; Ryan Sander; Sertac Karaman; Daniela Rus (CoRL, 2020)

Deep Orientation Uncertainty Learning based on a Bingham Loss. - Igor Gilitschenski; Roshni Sahoo; Wilko Schwarting; Alexander Amini; Sertac Karaman; Daniela Rus (ICLR, 2020)

Exploiting Semantic and Public Prior Information in MonoSLAM. - Chenxi Ye; Yiduo Wang 001; Ziwen Lu; Igor Gilitschenski; Martin P. Parsley; Simon J. Julier (IROS, 2020)

Learning Robust Control Policies for End-to-End Autonomous Driving From Data-Driven Simulation. - Alexander Amini; Igor Gilitschenski; Jacob Phillips; Julia Moseyko; Rohan Banerjee; Sertac Karaman; Daniela Rus (IEEE Robotics Autom. Lett., 2020)

Deep Context Maps: Agent Trajectory Prediction Using Location-Specific Latent Maps. - Igor Gilitschenski; Guy Rosman; Arjun Gupta; Sertac Karaman; Daniela Rus (IEEE Robotics Autom. Lett., 2020)

Autonomous Navigation in Inclement Weather Based on a Localizing Ground Penetrating Radar. - Teddy Ort; Igor Gilitschenski; Daniela Rus (IEEE Robotics Autom. Lett., 2020)

MapLite: Autonomous Intersection Navigation Without a Detailed Prior Map. - Teddy Ort; Krishna Murthy 001; Rohan Banerjee; Sai Krishna Gottipati; Dhaivat Bhatt; Igor Gilitschenski; Liam Paull; Daniela Rus (IEEE Robotics Autom. Lett., 2020)

Strength Through Diversity: Robust Behavior Learning via Mixture Policies. - Tim Seyde; Wilko Schwarting; Igor Gilitschenski; Markus Wulfmeier; Daniela Rus (CoRL, 2021)

Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies. - Tim Seyde; Igor Gilitschenski; Wilko Schwarting; Bartolomeo Stellato; Martin A. Riedmiller; Markus Wulfmeier; Daniela Rus (NeurIPS, 2021)

GROUNDED: The Localizing Ground Penetrating Radar Evaluation Dataset. - Teddy Ort; Igor Gilitschenski; Daniela Rus (Robotics: Science and Systems, 2021)

Vehicle Trajectory Prediction Using Generative Adversarial Network With Temporal Logic Syntax Tree Features. - Xiao Li 025; Guy Rosman; Igor Gilitschenski; Cristian Ioan Vasile; Jonathan A. DeCastro; Sertac Karaman; Daniela Rus (IEEE Robotics Autom. Lett., 2021)

Housekeep: Tidying Virtual Households Using Commonsense Reasoning. - Yash Kant; Arun Ramachandran; Sriram Yenamandra; Igor Gilitschenski; Dhruv Batra; Andrew Szot; Harsh Agrawal (ECCV (39), 2022)

LaTeRF: Label and Text Driven Object Radiance Fields. - Ashkan Mirzaei; Yash Kant; Jonathan Kelly; Igor Gilitschenski (ECCV (3), 2022)

VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles. - Alexander Amini; Tsun-Hsuan Wang; Igor Gilitschenski; Wilko Schwarting; Zhijian Liu; Song Han 003; Sertac Karaman; Daniela Rus (ICRA, 2022)

A Deep Concept Graph Network for Interaction-Aware Trajectory Prediction. - Yutong Ban; Xiao Li 025; Guy Rosman; Igor Gilitschenski; Ozanan R. Meireles; Sertac Karaman; Daniela Rus (ICRA, 2022)

HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling. - Xin Huang 018; Guy Rosman; Igor Gilitschenski; Ashkan Jasour; Stephen G. McGill; John J. Leonard; Brian C. Williams (ICRA, 2022)

Learning Interactive Driving Policies via Data-driven Simulation. - Tsun-Hsuan Wang; Alexander Amini; Wilko Schwarting; Igor Gilitschenski; Sertac Karaman; Daniela Rus (ICRA, 2022)

Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks. - Ryan Sander; Wilko Schwarting; Tim Seyde; Igor Gilitschenski; Sertac Karaman; Daniela Rus (L4DC, 2022)

See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction. - Maria Attarian; Advaya Gupta; Ziyi Zhou; Wei Yu; Igor Gilitschenski; Animesh Garg (CoRR, 2022)

Learning an Explainable Trajectory Generator Using the Automaton Generative Network (AGN). - Xiao Li 025; Guy Rosman; Igor Gilitschenski; Brandon Araki; Cristian-Ioan Vasile; Sertac Karaman; Daniela Rus (IEEE Robotics Autom. Lett., 2022)

MapLite 2.0: Online HD Map Inference Using a Prior SD Map. - Teddy Ort; Jeffrey M. Walls; Steven A. Parkison; Igor Gilitschenski; Daniela Rus (IEEE Robotics Autom. Lett., 2022)

Sensitivity-Informed Provable Pruning of Neural Networks. - Cenk Baykal; Lucas Liebenwein; Igor Gilitschenski; Dan Feldman; Daniela Rus (SIAM J. Math. Data Sci., 2022)

Geometry Matching for Multi-Embodiment Grasping. - Maria Attarian; Muhammad Adil Asif; Jingzhou Liu; Ruthrash Hari; Animesh Garg; Igor Gilitschenski; Jonathan Tompson (CoRL, 2023)

Dynamic Multi-Team Racing: Competitive Driving on 1/10-th Scale Vehicles via Learning in Simulation. - Peter Werner; Tim Seyde; Paul Drews; Thomas Matrai Balch; Igor Gilitschenski; Wilko Schwarting; Guy Rosman; Sertac Karaman; Daniela Rus (CoRL, 2023)

Invertible Neural Skinning. - Yash Kant; Aliaksandr Siarohin; Riza Alp Güler; Menglei Chai; Jian Ren 005; Sergey Tulyakov; Igor Gilitschenski (CVPR, 2023)

CAMM: Building Category-Agnostic and Animatable 3D Models from Monocular Videos. - Tianshu Kuai; Akash Karthikeyan; Yash Kant; Ashkan Mirzaei; Igor Gilitschenski (CVPR Workshops, 2023)

SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields. - Ashkan Mirzaei; Tristan Aumentado-Armstrong; Konstantinos G. Derpanis; Jonathan Kelly; Marcus A. Brubaker; Igor Gilitschenski; Alex Levinshtein (CVPR, 2023)

SparsePose: Sparse-View Camera Pose Regression and Refinement. - Samarth Sinha; Jason Y. Zhang 001; Andrea Tagliasacchi; Igor Gilitschenski; David B. Lindell (CVPR, 2023)

Reference-guided Controllable Inpainting of Neural Radiance Fields. - Ashkan Mirzaei; Tristan Aumentado-Armstrong; Marcus A. Brubaker; Jonathan Kelly; Alex Levinshtein; Konstantinos G. Derpanis; Igor Gilitschenski (ICCV, 2023)

Solving Continuous Control via Q-learning. - Tim Seyde; Peter Werner; Wilko Schwarting; Igor Gilitschenski; Martin A. Riedmiller; Daniela Rus; Markus Wulfmeier (ICLR, 2023)

trajdata: A Unified Interface to Multiple Human Trajectory Datasets. - Boris Ivanovic; Guanyu Song; Igor Gilitschenski; Marco Pavone 001 (NeurIPS, 2023)

SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models. - Ziyi Wu; Jingyu Hu; Wuyue Lu 002; Igor Gilitschenski; Animesh Garg (NeurIPS, 2023)

Repurposing Diffusion Inpainters for Novel View Synthesis. - Yash Kant; Aliaksandr Siarohin; Michael Vasilkovsky; Riza Alp Güler; Jian Ren 005; Sergey Tulyakov; Igor Gilitschenski (SIGGRAPH Asia, 2023)

Building Scalable Video Understanding Benchmarks through Sports. - Aniket Agarwal; Alex Zhang; Karthik Narasimhan; Igor Gilitschenski; Vishvak Murahari; Yash Kant (CoRR, 2023)

EventCLIP: Adapting CLIP for Event-based Object Recognition. - Ziyi Wu; Xudong Liu; Igor Gilitschenski (CoRR, 2023)

λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces. - Claas Voelcker; Arash Ahmadian; Romina Abachi; Igor Gilitschenski; Amir-massoud Farahmand (CoRR, 2023)

iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis. - Yash Kant; Aliaksandr Siarohin; Michael Vasilkovsky; Riza Alp Güler; Jian Ren 005; Sergey Tulyakov; Igor Gilitschenski (CoRR, 2023)

Reconstructive Latent-Space Neural Radiance Fields for Efficient 3D Scene Representations. - Tristan Aumentado-Armstrong; Ashkan Mirzaei; Marcus A. Brubaker; Jonathan Kelly; Alex Levinshtein; Konstantinos G. Derpanis; Igor Gilitschenski (CoRR, 2023)

Multi-Abstractive Neural Controller: An Efficient Hierarchical Control Architecture for Interactive Driving. - Xiao Li 025; Igor Gilitschenski; Guy Rosman; Sertac Karaman; Daniela Rus (IEEE Robotics Autom. Lett., 2023)

GROUNDED: A localizing ground penetrating radar evaluation dataset for learning to localize in inclement weather. - Teddy Ort; Igor Gilitschenski; Daniela Rus (Int. J. Robotics Res., 2023)

Producing and Leveraging Online Map Uncertainty in Trajectory Prediction. - Xunjiang Gu; Guanyu Song; Igor Gilitschenski; Marco Pavone 001; Boris Ivanovic (CVPR, 2024)

SPAD: Spatially Aware Multi-View Diffusers. - Yash Kant; Aliaksandr Siarohin; Ziyi Wu; Michael Vasilkovsky; Guocheng Qian; Jian Ren 005; Riza Alp Güler; Bernard Ghanem; Sergey Tulyakov; Igor Gilitschenski (CVPR, 2024)

LEOD: Label-Efficient Object Detection for Event Cameras. - Ziyi Wu; Mathias Gehrig; Qing Lyu 008; Xudong Liu; Igor Gilitschenski (CVPR, 2024)

Accelerating Online Mapping and Behavior Prediction via Direct BEV Feature Attention. - Xunjiang Gu; Guanyu Song; Igor Gilitschenski; Marco Pavone 001; Boris Ivanovic (ECCV (81), 2024)

Watch Your Steps: Local Image and Scene Editing by Text Instructions. - Ashkan Mirzaei; Tristan Aumentado-Armstrong; Marcus A. Brubaker; Jonathan Kelly; Alex Levinshtein; Konstantinos G. Derpanis; Igor Gilitschenski (ECCV (38), 2024)

NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking. - Daniel Dauner; Marcel Hallgarten; Tianyu Li; Xinshuo Weng; Zhiyu Huang; Zetong Yang; Hongyang Li 001; Igor Gilitschenski; Boris Ivanovic; Marco Pavone 001; Andreas Geiger 001; Kashyap Chitta (NeurIPS, 2024)

GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting. - Umangi Jain; Ashkan Mirzaei; Igor Gilitschenski (NeurIPS, 2024)

Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models. - Ziyi Wu; Yulia Rubanova; Rishabh Kabra; Drew A. Hudson; Igor Gilitschenski; Yusuf Aytar; Sjoerd van Steenkiste; Kelsey R. Allen; Thomas Kipf (NeurIPS, 2024)

Dissecting Deep RL with High Update Ratios: Combatting Value Divergence. - Marcel Hussing; Claas Voelcker; Igor Gilitschenski; Amir-massoud Farahmand; Eric Eaton (RLJ, 2024)

When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning. - Claas Voelcker; Tyler Kastner; Igor Gilitschenski; Amir-massoud Farahmand (RLJ, 2024)

Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers. - Vidhi Jain; Maria Attarian; Nikhil J. Joshi; Ayzaan Wahid; Danny Driess; Quan Vuong; Pannag R. Sanketi; Pierre Sermanet; Stefan Welker; Christine Chan; Igor Gilitschenski; Yonatan Bisk; et al. (Robotics: Science and Systems, 2024)

AvatarOne: Monocular 3D Human Animation. - Akash Karthikeyan; Robert Ren; Yash Kant; Igor Gilitschenski (WACV, 2024)

AToM: Amortized Text-to-Mesh using 2D Diffusion. - Guocheng Qian; Junli Cao; Aliaksandr Siarohin; Yash Kant; Chaoyang Wang 001; Michael Vasilkovsky; Hsin-Ying Lee 001; Yuwei Fang; Ivan Skorokhodov; Peiye Zhuang; Igor Gilitschenski; Jian Ren 005; et al. (CoRR, 2024)

SPAD : Spatially Aware Multiview Diffusers. - Yash Kant; Ziyi Wu; Michael Vasilkovsky; Guocheng Qian; Jian Ren 005; Riza Alp Güler; Bernard Ghanem; Sergey Tulyakov; Igor Gilitschenski; Aliaksandr Siarohin (CoRR, 2024)

Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence. - Marcel Hussing; Claas Voelcker; Igor Gilitschenski; Amir-massoud Farahmand; Eric Eaton (CoRR, 2024)

RefFusion: Reference Adapted Diffusion Models for 3D Scene Inpainting. - Ashkan Mirzaei; Riccardo de Lutio; Seung Wook Kim 001; David Acuna; Jonathan Kelly; Sanja Fidler; Igor Gilitschenski; Zan Gojcic (CoRR, 2024)

Realistic Evaluation of Model Merging for Compositional Generalization. - Derek Tam; Yash Kant; Brian Lester; Igor Gilitschenski; Colin Raffel (CoRR, 2024)

Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos. - Hanxue Liang; Jiawei Ren 001; Ashkan Mirzaei; Antonio Torralba 001; Ziwei Liu 002; Igor Gilitschenski; Sanja Fidler; Cengiz Öztireli; Huan Ling; Zan Gojcic; Jiahui Huang (CoRR, 2024)

GeoMatch++: Morphology Conditioned Geometry Matching for Multi-Embodiment Grasping. - Yunze Wei; Maria Attarian; Igor Gilitschenski (CoRR, 2024)

CTRL-D: Controllable Dynamic 3D Scene Editing with Personalized 2D Diffusion. - Kai He; Chin-Hsuan Wu; Igor Gilitschenski (CVPR, 2025)

Pippo: High-Resolution Multi-View Humans from a Single Image. - Yash Kant; Ethan Weber; Jin Kyu Kim; Rawal Khirodkar; Su Zhaoen; Julieta Martinez 001; Igor Gilitschenski; Shunsuke Saito; Timur M. Bagautdinov (CVPR, 2025)

Mind the Time: Temporally-Controlled Multi-Event Video Generation. - Ziyi Wu; Aliaksandr Siarohin; Willi Menapace; Ivan Skorokhodov; Yuwei Fang; Varnith Chordia; Igor Gilitschenski; Sergey Tulyakov (CVPR, 2025)

EventSplat: 3D Gaussian Splatting from Moving Event Cameras for Real-time Rendering. - Toshiya Yura; Ashkan Mirzaei; Igor Gilitschenski (CVPR, 2025)

SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation. - Koichi Namekata; Sherwin Bahmani; Ziyi Wu; Yash Kant; Igor Gilitschenski; David B. Lindell (ICLR, 2025)

MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL. - Claas Voelcker; Marcel Hussing; Eric Eaton; Amir-massoud Farahmand; Igor Gilitschenski (ICLR, 2025)

Towards Unsupervised Blind Face Restoration Using Diffusion Prior. - Tianshu Kuai; Sina Honari; Igor Gilitschenski; Alex Levinshtein (WACV, 2025)

MORE: Mobile Manipulation Rearrangement Through Grounded Language Reasoning. - Mohammad Mohammadi; Daniel Honerkamp; Martin Büchner; Matteo Cassinelli; Tim Welschehold; Fabien Despinoy; Igor Gilitschenski; Abhinav Valada (CoRR, 2025)

Calibrated Value-Aware Model Learning with Stochastic Environment Models. - Claas Voelcker; Anastasiia Pedan; Arash Ahmadian; Romina Abachi; Igor Gilitschenski; Amir-massoud Farahmand (CoRR, 2025)

DenseDPO: Fine-Grained Temporal Preference Optimization for Video Diffusion Models. - Ziyi Wu; Anil Kag; Ivan Skorokhodov; Willi Menapace; Ashkan Mirzaei; Igor Gilitschenski; Sergey Tulyakov; Aliaksandr Siarohin (CoRR, 2025)

Pseudo-Simulation for Autonomous Driving. - Wei Cao; Marcel Hallgarten; Tianyu Li; Daniel Dauner; Xunjiang Gu; Caojun Wang; Yakov Miron; Marco Aiello 001; Hongyang Li 001; Igor Gilitschenski; Boris Ivanovic; Marco Pavone 001; et al. (CoRR, 2025)

SAFE: Multitask Failure Detection for Vision-Language-Action Models. - Qiao Gu; Yuanliang Ju; Shengxiang Sun; Igor Gilitschenski; Haruki Nishimura; Masha Itkina; Florian Shkurti (CoRR, 2025)

UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting. - Kai He; Ruofan Liang; Jacob Munkberg; Jon Hasselgren; Nandita Vijaykumar; Alexander Keller 001; Sanja Fidler; Igor Gilitschenski; Zan Gojcic; Zian Wang (CoRR, 2025)

Box Pose and Shape Estimation and Domain Adaptation for Large-Scale Warehouse Automation. - Xihang Yu; Rajat Talak; Jingnan Shi; Ulrich Viereck; Igor Gilitschenski; Luca Carlone (CoRR, 2025)

S2Edit: Text-Guided Image Editing with Precise Semantic and Spatial Control. - Xudong Liu; Zikun Chen; Ruowei Jiang; Ziyi Wu; Kejia Yin; Han Zhao 002; Parham Aarabi; Igor Gilitschenski (CoRR, 2025)

Relative Entropy Pathwise Policy Optimization. - Claas Voelcker; Axel Brunnbauer; Marcel Hussing; Michal Nauman; Pieter Abbeel; Eric Eaton; Radu Grosu; Amir-massoud Farahmand; Igor Gilitschenski (CoRR, 2025)

AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework. - Yu Yao; Salil Bhatnagar; Markus Mazzola; Vasileios Belagiannis; Igor Gilitschenski; Luigi Palmieri; Simon Razniewski; Marcel Hallgarten (CoRR, 2025)

Delving into Mapping Uncertainty for Mapless Trajectory Prediction. - Zongzheng Zhang; Xuchong Qiu; Boran Zhang; Guantian Zheng; Xunjiang Gu; Guoxuan Chi; Huan-ang Gao; Leichen Wang; Ziming Liu; Xinrun Li; Igor Gilitschenski; Hongyang Li 001; et al. (CoRR, 2025)

TESPEC: Temporally-Enhanced Self-Supervised Pretraining for Event Cameras. - Mohammad Mohammadi; Ziyi Wu; Igor Gilitschenski (CoRR, 2025)