Igor Gilitschenski
Assistant Professor
Leads the Toronto Intelligent Systems Lab, working on robot learning, multi-modal perception and robust autonomy.
Igor Gilitschenski's lab at Toronto works on manipulation & robot learning, robot perception & SLAM and vision-language & multimodal. 49 papers since 2023, 38 at top venues, mostly CVPR and NeurIPS. 11 PhD students and 7 master's students. 26 alumni, most often to ByteDance and NVIDIA. Applications close .
At a glance
- papers, 2023–2026
- 13/ year
- at T1 venues
- 78%
- PhD students
- 11
- MS students
- 7
- alumni listed
- 26
Papers by yearfrom the lab homepage, 2023–2026
- 7 papers2026 · T1 4 · collecting
- 20 papers2025 · T1 20
- 10 papers2024 · T1 6
- 12 papers2023 · T1 8
T1 venuesOtherVenues: CVPR, NeurIPS, ICLR, CoRL, IROS
Research focuspaper titles that use each topic's words
- Manipulation & robot learning10 papers
- Vision-language & multimodal2 papers
- Robot perception & SLAM0 papers
- toronto0 papers
- multi-modal0 papers
Paper list
From the lab homepage.
20267 papers
- CVPR (T1)Material Magic Wand: Material-Aware Grouping of 3D Parts in Untextured Meshes (opens in a new tab)
- RLCModification-Considering Value Learning for Reward Hacking Mitigation in RL (opens in a new tab)
- TMLR (T1)Realistic Evaluation of Model Merging for Compositional Generalization (opens in a new tab)
- ICLR (T1)Relative Entropy Pathwise Policy Optimization (opens in a new tab)
- ICML (T1)Test-Time Graph Search for Goal-Conditioned Reinforcement Learning (opens in a new tab)
- 3DVVibES: Induced Vibration for Persistent Event-Based Sensing (opens in a new tab)
- ICCPWhy Low-Light Cameras Go Color Blind: Removing Color Bias in Raw Denoising (opens in a new tab)
202520 papers
- IROS (T1)AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework (opens in a new tab)
- ICML (T1)Calibrated Value-Aware Model Learning with Probabilistic Environment Models (opens in a new tab)
- CVPR (T1)CTRL-D: Controllable Dynamic 3D Scene Editing with Personalized 2D Diffusion (opens in a new tab)
- IROS (T1)Delving into Mapping Uncertainty for Mapless Trajectory Prediction (opens in a new tab)
- NeurIPS (T1)DenseDPO: Fine-Grained Temporal Preference Optimization for Video Diffusion Models (opens in a new tab)
- CVPR (T1)EventSplat: 3D Gaussian Splatting from Moving Event Cameras for Real-time Rendering (opens in a new tab)
- NeurIPS (T1)Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos (opens in a new tab)
- NeurIPS (T1)GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting (opens in a new tab)
- NeurIPS (T1)Kai He, Ruofan Liang, Jacob Munkberg, Jon Hasselgren, Nandita Vijaykumar, Alexander Keller, Sanja Fidler, Igor Gilitschenski, Zan Gojcic, Zian Wang (2025)
- NeurIPS (T1)LuxDiT: Lighting Estimation with Video Diffusion Transformer (opens in a new tab)
- ICLR (T1)MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL (opens in a new tab)
- CVPR (T1)Mind the Time: Temporally-Controlled Multi-Event Video Generation (opens in a new tab)
202410 papers
- ECCV (T1)Accelerating Online Mapping and Behavior Prediction via Direct BEV Feature Attention (opens in a new tab)
- WACVAvatarOne: Monocular 3D Human Animation (opens in a new tab)
- RLCDissecting Deep RL with High Update Ratios: Combatting Value Divergence (opens in a new tab)
- CVPR (T1)LEOD: Label-Efficient Object Detection for Event Cameras (opens in a new tab)
- CVPR (T1)Producing and Leveraging Online Map Uncertainty in Trajectory Prediction (opens in a new tab)
- CVPR (T1)SPAD: Spatially Aware Multi-View Diffusers (opens in a new tab)
- WACVTowards Unsupervised Blind Face Restoration using Diffusion Prior (opens in a new tab)
- RSS (T1)Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers (opens in a new tab)
- ECCV (T1)Watch Your Steps: Local Image and Scene Editing by Text Instruction (opens in a new tab)
- RLCWhen does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning (opens in a new tab)
202312 papers
- CoRL (T1)Dynamic Multi-Team Racing: Competitive Driving on 1/10-th Scale Vehicles via Learning in Simulation (opens in a new tab)
- CoRL (T1)Geometry Matching for Multi-Embodiment Grasping (opens in a new tab)
- IJRR* (acceptedGROUNDED: A Localizing Ground Penetrating Radar Evaluation Dataset for Learning to Localize in Inclement Weather (opens in a new tab)
- CVPR (T1)Invertible Neural Skinning (opens in a new tab)
- SIGGRAPH Asia ConfiNVS: Repurposing Diffusion Inpainters for Novel View Synthesis (opens in a new tab)
- RA-LMulti-Abstractive Neural Controller: An Efficient Hierarchical Control Architecture for Interactive Driving (opens in a new tab)
- ICCV (T1)Reference-guided Controllable Inpainting of Neural Radiance Fields (opens in a new tab)
- NeurIPS (T1)SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models (opens in a new tab)
- ICLR (T1)Solving Continuous Control via Q-Learning (opens in a new tab)
- CVPR (T1)SparsePose: Sparse-View Camera Pose Regression and Refinement (opens in a new tab)
- CVPR (T1)SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields (opens in a new tab)
- NeurIPS-DBtrajdata: A Unified Interface to Multiple Human Trajectory Datasets (opens in a new tab)
Where alumni went26 listed, 50% to industry
Industry 3Academia 3
Most often to
- ByteDance
- NVIDIA
- Software Eng.
Apply to TorontoFall 2027
Computer Science MSc/PhD
- Round
- Single round (Dec 1)
- Opens
- —
- GRE
- optional
- English
- TOEFL/IELTS if applicable
- Fee
- CAD 135
Confirmed on the program page.
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