283 citations · 613 across the 31 of their papers we have counts for
35 papers
Overpainting: Localized Context-aware Diffusion Image Editing
Sam Sartor, Iliyan Georgiev, Michael Fischer +2
We present "overpainting", an image editing operation which offers both control over the location of the edit and awareness of the previous content in that location. The overpainte…
ResEdit: Residual embeddings for precise generative image editing
Ahmet Canberk Baykal, Valentin Deschaintre, Yannick Hold-Geoffroy +4
Conditional diffusion image generators can be repurposed for editing through inversion, without the need for large-scale paired fine-tuning data. However, producing high-quality, t…
MAOAM: Unified Object and Material Selection with Vision-Language Models
Jaden Park, Valentin Deschaintre, Jason Kuen +5
Selection is a core operation in interactive image editing. To be practical, a user should be able to specify and disambiguate the desired selection region through either text or c…
V-RGBX: Video Editing with Accurate Controls over Intrinsic Properties
Ye Fang, Tong Wu, Valentin Deschaintre +6
Large-scale video generation models have shown remarkable potential in modeling photorealistic appearance and lighting interactions in real-world scenes. However, a closed-loop fra…
GimbalDiffusion: Gravity-Aware Camera Control for Video Generation
Frédéric Fortier-Chouinard, Yannick Hold-Geoffroy, Valentin Deschaintre +2
Recent progress in text-to-video generation has achieved remarkable realism, yet fine-grained control over camera motion and orientation remains elusive, especially with extreme tr…
UniLight: A Unified Representation for Lighting
Zitian Zhang, Iliyan Georgiev, Michael Fischer +3
Lighting has a strong influence on visual appearance, yet understanding and representing lighting in images remains notoriously difficult. Various lighting representations exist, s…
RealMat: Realistic Materials with Diffusion and Reinforcement Learning
Xilong Zhou, Pedro Figueiredo, Miloš Hašan +4
Generative models for high-quality materials are particularly desirable to make 3D content authoring more accessible. However, the majority of material generation methods are train…
Fine-Grained Spatially Varying Material Selection in Images
Julia Guerrero-Viu, Michael Fischer, Iliyan Georgiev +4
Selection is the first step in many image editing processes, enabling faster and simpler modifications of all pixels sharing a common modality. In this work, we present a method fo…
IntrinsicEdit: Precise generative image manipulation in intrinsic space
Linjie Lyu, Valentin Deschaintre, Yannick Hold-Geoffroy +5
Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. However, these interfaces lack prec…
MatSwap: Light-aware material transfers in images
Ivan Lopes, Valentin Deschaintre, Yannick Hold-Geoffroy +1
We present MatSwap, a method to transfer materials to designated surfaces in an image photorealistically. Such a task is non-trivial due to the large entanglement of material appea…
MaterialPicker: Multi-Modal DiT-Based Material Generation
Xiaohe Ma, Valentin Deschaintre, Miloš Hašan +4
High-quality material generation is key for virtual environment authoring and inverse rendering. We propose MaterialPicker, a multi-modal material generator leveraging a Diffusion…
SAMa: Material-aware 3D Selection and Segmentation
Michael Fischer, Iliyan Georgiev, Thibault Groueix +3
Decomposing 3D assets into material parts is a common task for artists, yet remains a highly manual process. In this work, we introduce Select Any Material (SAMa), a material selec…
Uncertainty for SVBRDF Acquisition using Frequency Analysis
Ruben Wiersma, Julien Philip, Miloš Hašan +4
This paper aims to quantify uncertainty for SVBRDF acquisition in multi-view captures. Under uncontrolled illumination and unstructured viewpoints, there is no guarantee that the o…
TexSliders: Diffusion-Based Texture Editing in CLIP Space
Julia Guerrero-Viu, Milos Hasan, Arthur Roullier +6
Generative models have enabled intuitive image creation and manipulation using natural language. In particular, diffusion models have recently shown remarkable results for natural…
RGBX: Image decomposition and synthesis using material- and lighting-aware diffusion models
Zheng Zeng, Valentin Deschaintre, Iliyan Georgiev +5
The three areas of realistic forward rendering, per-pixel inverse rendering, and generative image synthesis may seem like separate and unrelated sub-fields of graphics and vision.…
MatAtlas: Text-driven Consistent Geometry Texturing and Material Assignment
Duygu Ceylan, Valentin Deschaintre, Thibault Groueix +5
We present MatAtlas, a method for consistent text-guided 3D model texturing. Following recent progress we leverage a large scale text-to-image generation model (e.g., Stable Diffus…
MeshLRM: Large Reconstruction Model for High-Quality Meshes
Xinyue Wei, Kai Zhang, Sai Bi +6
We propose MeshLRM, a novel LRM-based approach that can reconstruct a high-quality mesh from merely four input images in less than one second. Different from previous large reconst…
MatSynth: A Modern PBR Materials Dataset
Giuseppe Vecchio, Valentin Deschaintre
We introduce MatSynth, a dataset of 4,000+ CC0 ultra-high resolution PBR materials. Materials are crucial components of virtual relightable assets, defining the interaction of ligh…
ControlMat: A Controlled Generative Approach to Material Capture
Giuseppe Vecchio, Rosalie Martin, Arthur Roullier +4
Material reconstruction from a photograph is a key component of 3D content creation democratization. We propose to formulate this ill-posed problem as a controlled synthesis one, l…
The Visual Language of Fabrics
Valentin Deschaintre, Julia Guerrero-Viu, Diego Gutierrez +2
We introduce text2fabric, a novel dataset that links free-text descriptions to various fabric materials. The dataset comprises 15,000 natural language descriptions associated to 3,…
PSDR-Room: Single Photo to Scene using Differentiable Rendering
Kai Yan, Fujun Luan, MiloŠ HaŠAn +3
A 3D digital scene contains many components: lights, materials and geometries, interacting to reach the desired appearance. Staging such a scene is time-consuming and requires both…
Floaters No More: Radiance Field Gradient Scaling for Improved Near-Camera Training
Julien Philip, Valentin Deschaintre
NeRF acquisition typically requires careful choice of near planes for the different cameras or suffers from background collapse, creating floating artifacts on the edges of the cap…
PhotoMat: A Material Generator Learned from Single Flash Photos
Xilong Zhou, Miloš Hašan, Valentin Deschaintre +4
Authoring high-quality digital materials is key to realism in 3D rendering. Previous generative models for materials have been trained exclusively on synthetic data; such data is l…
Materialistic: Selecting Similar Materials in Images
Prafull Sharma, Julien Philip, Michaël Gharbi +3
Separating an image into meaningful underlying components is a crucial first step for both editing and understanding images. We present a method capable of selecting the regions of…