Leonidas Guibas
Paul Pigott Professor of Engineering
Studies 3D geometric data analysis, shape understanding and 3D scene generation.
Leonidas Guibas's lab at Stanford works on 3D vision & neural rendering, geometry processing & modeling and generative 3D & visual content. 114 papers since 2023, 102 at top venues, mostly CVPR and ICCV. Applications close .
At a glance
- papers, 2023–2026
- 30/ year
- at T1 venues
- 89%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 17 papers2026 · T1 13 · collecting
- 31 papers2025 · T1 27
- 37 papers2024 · T1 35
- 29 papers2023 · T1 27
T1 venuesOtherVenues: CVPR, ICCV, ECCV, ICLR, NeurIPS
Research focuspaper titles that use each topic's words
- 3D vision & neural rendering23 papers
- Generative 3D & visual content10 papers
- Geometry processing & modeling7 papers
- shape7 papers
- data analysis0 papers
Paper list
From DBLP.
202617 papers
- Trans. Mach. Learn. Res.Denoising Hamiltonian Network for Physical Reasoning (opens in a new tab)
- ICRA (T1)DOT-Sim: Differentiable Optical Tactile Simulation with Precise Real-to-Sim Physical Calibration (opens in a new tab)
- ICLR (T1)Dynamic Reflections: Probing Video Representations with Text Alignment (opens in a new tab)
- CVPR (T1)FUN REC * Reconstructing Functional 3D Scenes from Egocentric Interaction Videos (opens in a new tab)
- ECCV (T1)GaussianLens: Localized High-Resolution Reconstruction via On-Demand Gaussian Densification (opens in a new tab)
- J. Comput. Biol.Learning Protein Structure Representation with Orientation-Aware Networks (opens in a new tab)
- SIGGRAPH (T1)MeshFlow: Mesh Generation with Equivariant Flow Matching (opens in a new tab)
- ICLR (T1)Mixture of Contexts for Long Video Generation (opens in a new tab)
- 3DVPASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers (opens in a new tab)
- ICLR (T1)pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation (opens in a new tab)
- IJCV (T1)PosePAL: Efficient Animal Pose Labeling Using Point Trackers (opens in a new tab)
- CVPR (T1)RINO: Rotation-Invariant Non-Rigid Correspondences (opens in a new tab)
202531 papers
- CVPR (T1)AIpparel: A Multimodal Foundation Model for Digital Garments (opens in a new tab)
- ICCV (T1)AllTracker: Efficient Dense Point Tracking at High Resolution (opens in a new tab)
- Comput. Graph. ForumAn Efficient Global-to-Local Rotation Optimization Approach via Spherical Harmonics (opens in a new tab)
- CVPR (T1)BlenderGym: Benchmarking Foundational Model Systems for Graphics Editing (opens in a new tab)
- ICCV (T1)CL-Splats: Continual Learning of Gaussian Splatting with Local Optimization (opens in a new tab)
- CVPR (T1)Diffusion Self-Distillation for Zero-Shot Customized Image Generation (opens in a new tab)
- CVPR (T1)Feature4X: Bridging Any Monocular Video to 4D Agentic AI with Versatile Gaussian Feature Fields (opens in a new tab)
- CVPR (T1)FirePlace: Geometric Refinements of LLM Common Sense Reasoning for 3D Object Placement (opens in a new tab)
- ICML (T1)Gaussian Mixture Flow Matching Models (opens in a new tab)
- TOG (T1)GenAnalysis: Joint Shape Analysis by Learning Man-Made Shape Generators with Deformation Regularizations (opens in a new tab)
- ICCV (T1)Global Motion Corresponder for 3D Point-Based Scene Interpolation Under Large Motion (opens in a new tab)
- CVPR (T1)GroomLight: Hybrid Inverse Rendering for Relightable Human Hair Appearance Modeling (opens in a new tab)
202437 papers
- CVPR (T1)4D-fy: Text-to-4D Generation Using Hybrid Score Distillation Sampling (opens in a new tab)
- NeurIPS (T1)ActAnywhere: Subject-Aware Video Background Generation (opens in a new tab)
- Int. J. Robotics Res.Action-conditional implicit visual dynamics for deformable object manipulation (opens in a new tab)
- IROS (T1)AO-Grasp: Articulated Object Grasp Generation (opens in a new tab)
- ECCV (T1)ArtVLM: Attribute Recognition Through Vision-Based Prefix Language Modeling (opens in a new tab)
- ECCV (T1)BlenderAlchemy: Editing 3D Graphics with Vision-Language Models (opens in a new tab)
- CVPR (T1)CAD : Photorealistic 3D Generation via Adversarial Distillation (opens in a new tab)
- CVPR (T1)Category-Level Multi-Part Multi-Joint 3D Shape Assembly (opens in a new tab)
- NeurIPS (T1)Collaborative Video Diffusion: Consistent Multi-video Generation with Camera Control (opens in a new tab)
- ECCV (T1)CONDENSE: Consistent 2D/3D Pre-training for Dense and Sparse Features from Multi-View Images (opens in a new tab)
- CVPR (T1)CurveCloudNet: Processing Point Clouds with 1D Structure (opens in a new tab)
- CoRL (T1)D3RoMa: Disparity Diffusion-based Depth Sensing for Material-Agnostic Robotic Manipulation (opens in a new tab)
202329 papers
- Trans. Mach. Learn. Res.3D-Aware Video Generation (opens in a new tab)
- CVPR (T1)Affection: Learning Affective Explanations for Real-World Visual Data (opens in a new tab)
- CVPR (T1)ALTO: Alternating Latent Topologies for Implicit 3D Reconstruction (opens in a new tab)
- NeurIPS (T1)Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance (opens in a new tab)
- ICCV (T1)CC3D: Layout-Conditioned Generation of Compositional 3D Scenes (opens in a new tab)
- ICCV (T1)COPILOT: Human-Environment Collision Prediction and Localization from Egocentric Videos (opens in a new tab)
- ICCV (T1)DiffFacto: Controllable Part-Based 3D Point Cloud Generation with Cross Diffusion (opens in a new tab)
- TOG (T1)DSG-Net: Learning Disentangled Structure and Geometry for 3D Shape Generation (opens in a new tab)
- CVPR (T1)EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation Without Scene Supervision (opens in a new tab)
- CoRL (T1)FindThis: Language-Driven Object Disambiguation in Indoor Environments (opens in a new tab)
- CVPR (T1)Generating Part-Aware Editable 3D Shapes without 3D Supervision (opens in a new tab)
- CVPR (T1)GINA-3D: Learning to Generate Implicit Neural Assets in the Wild (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to StanfordFall 2027
Stanford Computer Science PhD
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Data
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