Andrea Vedaldi
Professor of Computer Vision and Machine Learning
Develops computer vision methods that understand image and video semantics and 3D geometry with little or no manual supervision.
Andrea Vedaldi's lab at Oxford works on 3D vision & neural rendering and video understanding. 86 papers since 2023, 74 at top venues, mostly CVPR and ICCV. Applications close .
At a glance
- papers, 2023–2026
- 22/ year
- at T1 venues
- 86%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 19 papers2026 · T1 17 · collecting
- 24 papers2025 · T1 20
- 22 papers2024 · T1 18
- 21 papers2023 · T1 19
T1 venuesOtherVenues: CVPR, ICCV, ECCV, NeurIPS, 3DV
Research focuspaper titles that use each topic's words
- 3D vision & neural rendering13 papers
- Video understanding9 papers
- vision methods0 papers
- little0 papers
- semantics0 papers
Paper list
From DBLP.
202619 papers
- CVPR (T1)CoWTracker: Tracking by Warping instead of Correlation (opens in a new tab)
- Trans. Mach. Learn. Res.DINOv3 (opens in a new tab)
- ECCV (T1)Free-Range Gaussians: Non-Grid-Aligned Generative 3D Gaussian Reconstruction (opens in a new tab)
- SIGGRAPH (T1)Go-with-the-Track: Video Compositing and Motion Control with Point Tracking (opens in a new tab)
- CVPR (T1)LagerNVS: Latent Geometry for Fully Neural Real-time Novel View Synthesis (opens in a new tab)
- CVPR (T1)LaVR: Scene Latent Conditioned Generative Video Trajectory Re-Rendering using Large 4D Reconstruction Models (opens in a new tab)
- CVPR (T1)Mesh4D: 4D Mesh Reconstruction and Tracking from Monocular Video (opens in a new tab)
- CVPR (T1)MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer (opens in a new tab)
- ECCV (T1)MeshReGen: A Unified 3D Geometry Regeneration Framework (opens in a new tab)
- ICLR (T1)NOVA3R: Non-pixel-aligned Visual Transformer for Amodal 3D Reconstruction (opens in a new tab)
- CVPR (T1)Particulate: Feed-Forward 3D Object Articulation (opens in a new tab)
- CVPR (T1)Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning (opens in a new tab)
202524 papers
- CVPR (T1)3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes (opens in a new tab)
- ICCV (T1)Amodal3R: Amodal 3D Reconstruction from Occluded 2D Images (opens in a new tab)
- NeurIPS (T1)AutoPartGen: Autoregressive 3D Part Generation and Discovery (opens in a new tab)
- ICCV (T1)Back on Track: Bundle Adjustment for Dynamic Scene Reconstruction (opens in a new tab)
- 3DVCatFree3D: Category-Agnostic 3D Object Detection with Diffusion (opens in a new tab)
- ICCV (T1)CoTracker3: Simpler and Better Point Tracking by Pseudo-Labeling Real Videos (opens in a new tab)
- ICCV (T1)DSO: Aligning 3D Generators with Simulation Feedback for Physical Soundness (opens in a new tab)
- CVPR (T1)DualPM: Dual Posed-Canonical Point Maps for 3D Shape and Pose Reconstruction (opens in a new tab)
- ICCV (T1)Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction (opens in a new tab)
- 3DVFlash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image (opens in a new tab)
- ICML (T1)Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation (opens in a new tab)
- ICCV (T1)Geo4D: Leveraging Video Generators for Geometric 4D Scene Reconstruction (opens in a new tab)
202422 papers
- ACCV3D-Aware Instance Segmentation and Tracking in Egocentric Videos (opens in a new tab)
- ECCV (T1)CoTracker: It Is Better to Track Together (opens in a new tab)
- ECCV (T1)DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editing (opens in a new tab)
- ECCV (T1)Diffusion Models for Open-Vocabulary Segmentation (opens in a new tab)
- ECCV (T1)DragAPart: Learning a Part-Level Motion Prior for Articulated Objects (opens in a new tab)
- 3DVFarm3D: Learning Articulated 3D Animals by Distilling 2D Diffusion (opens in a new tab)
- CVPR (T1)Free3D: Consistent Novel View Synthesis Without 3D Representation (opens in a new tab)
- CVPR (T1)GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering (opens in a new tab)
- ECCV (T1)GOEmbed: Gradient Origin Embeddings for Representation Agnostic 3D Feature Learning (opens in a new tab)
- ICML (T1)IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation (opens in a new tab)
- ECCV (T1)Instant Uncertainty Calibration of NeRFs Using a Meta-calibrator (opens in a new tab)
- NeurIPS (T1)Learning Segmentation from Point Trajectories (opens in a new tab)
202321 papers
- CVPR (T1)Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories (opens in a new tab)
- CVPR (T1)Continual Detection Transformer for Incremental Object Detection (opens in a new tab)
- NeurIPS (T1)Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion (opens in a new tab)
- IJCV (T1)DOVE: Learning Deformable 3D Objects by Watching Videos (opens in a new tab)
- CVPR (T1)DynamicStereo: Consistent Dynamic Depth from Stereo Videos (opens in a new tab)
- NeurIPS (T1)EPIC Fields: Marrying 3D Geometry and Video Understanding (opens in a new tab)
- CVPR (T1)HOLODIFFUSION: Training a 3D Diffusion Model Using 2D Images (opens in a new tab)
- ICCV (T1)HoloFusion: Towards Photo-realistic 3D Generative Modeling (opens in a new tab)
- ICCV WorkshopLearning Universal Semantic Correspondences with No Supervision and Automatic Data Curation (opens in a new tab)
- CVPR (T1)MagicPony: Learning Articulated 3D Animals in the Wild (opens in a new tab)
- NeurIPS (T1)No Representation Rules Them All in Category Discovery (opens in a new tab)
- CVPR (T1)Novel-View Acoustic Synthesis (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Data
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