Frédo Durand
Amar Bose Professor of Computing
Studies picture generation and computational photography, including differentiable rendering, compilers for high-performance imaging, and video magnification.
Frédo Durand's lab at MIT works on rendering & appearance and computational imaging & photography. 17 papers since 2023, 13 at top venues, mostly CVPR and TOG. 55 alumni. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 76%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 55
Papers by yearfrom DBLP, 2023–2026
- 1 papers2026 · T1 1 · collecting
- 6 papers2025 · T1 4
- 4 papers2024 · T1 4
- 6 papers2023 · T1 4
T1 venuesOtherVenues: CVPR, TOG, NeurIPS, ICCV, ICLR
Research focuspaper titles that use each topic's words
- Rendering & appearance2 papers
- differentiable1 paper
- Computational imaging & photography0 papers
- differentiable rendering0 papers
- photography0 papers
Paper list
From DBLP.
20261 paper
20256 papers
- EGSRAn evaluation of SVBRDF Prediction from Generative Image Models for Appearance Modeling of 3D Scenes (opens in a new tab)
- EGSRContent-Aware Texturing for Gaussian Splatting (opens in a new tab)
- ICCV (T1)Cycle Consistency as Reward: Learning Image-Text Alignment Without Human Preferences (opens in a new tab)
- IJCV (T1)FastComposer: Tuning-Free Multi-subject Image Generation with Localized Attention (opens in a new tab)
- CVPR (T1)From Slow Bidirectional to Fast Autoregressive Video Diffusion Models (opens in a new tab)
- SIGGRAPH (T1)Splat and Replace: 3D Reconstruction with Repetitive Elements (opens in a new tab)
20244 papers
- CVPR (T1)Alchemist: Parametric Control of Material Properties with Diffusion Models (opens in a new tab)
- NSDI (T1)Gemino: Practical and Robust Neural Compression for Video Conferencing (opens in a new tab)
- NeurIPS (T1)Improved Distribution Matching Distillation for Fast Image Synthesis (opens in a new tab)
- CVPR (T1)One-Step Diffusion with Distribution Matching Distillation (opens in a new tab)
20236 papers
- WACVCan Shadows Reveal Biometric Informationƒ (opens in a new tab)
- NeurIPS (T1)Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision (opens in a new tab)
- TOG (T1)Materialistic: Selecting Similar Materials in Images (opens in a new tab)
- ICLR (T1)Neural Groundplans: Persistent Neural Scene Representations from a Single Image (opens in a new tab)
- TOG (T1)SLANG.D: Fast, Modular and Differentiable Shader Programming (opens in a new tab)
- Trans. Mach. Learn. Res.Unsupervised Discovery and Composition of Object Light Fields (opens in a new tab)
Where alumni went55 listed
Apply to MITFall 2027
MIT EECS Computer Science PhD
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