32 citations · 35 across the 10 of their papers we have counts for
12 papers
Differentiable Polarized Path Tracing
Pramod Rao, Jérémy Riviere, Xilong Zhou +6
Physically based differentiable rendering has proven to be a powerful tool for inverse rendering problems (e.g., 3D reconstruction, reflectance estimation, lighting estimation). Ho…
AlbedoEdit: Unified Instance-Level Video Editing with Albedo Guidance
Xilong Zhou, Bao-Huy Nguyen, Zheng Zeng +6
Video generative models have achieved remarkable progress in synthesizing photorealistic video sequences. However, enabling broader and more creative downstream applications requir…
D-Rex : Diffusion Rendering for Relightable Expressive Avatars
Timo Teufel, Xilong Zhou, Umar Iqbal +4
We present D-Rex, a person-specific framework for photorealistic, relightable, expressive, and animatable full-body human avatars with free-viewpoint rendering. Existing methods fo…
OLATverse: A Large-scale Real-world Object Dataset with Precise Lighting Control
Xilong Zhou, Jianchun Chen, Pramod Rao +7
We introduce OLATverse, a large-scale dataset comprising around 9M images of 765 real-world objects, captured from multiple viewpoints under a diverse set of precisely controlled l…
3DPR: Single Image 3D Portrait Relight using Generative Priors
Pramod Rao, Abhimitra Meka, Xilong Zhou +11
Rendering novel, relit views of a human head, given a monocular portrait image as input, is an inherently underconstrained problem. The traditional graphics solution is to explicit…
Splat the Net: Radiance Fields with Splattable Neural Primitives
Xilong Zhou, Bao-Huy Nguyen, Loïc Magne +3
Radiance fields have emerged as a predominant representation for modeling 3D scene appearance. Neural formulations such as Neural Radiance Fields provide high expressivity but requ…
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…
HumanOLAT: A Large-Scale Dataset for Full-Body Human Relighting and Novel-View Synthesis
Timo Teufel, Pulkit Gera, Xilong Zhou +5
Simultaneous relighting and novel-view rendering of digital human representations is an important yet challenging task with numerous applications. Progress in this area has been si…
RI3D: Few-Shot Gaussian Splatting With Repair and Inpainting Diffusion Priors
Avinash Paliwal, Xilong Zhou, Wei Ye +3
In this paper, we propose RI3D, a novel 3DGS-based approach that harnesses the power of diffusion models to reconstruct high-quality novel views given a sparse set of input images.…
PanoDreamer: Optimization-Based Single Image to 360 3D Scene With Diffusion
Avinash Paliwal, Xilong Zhou, Andrii Tsarov +1
In this paper, we present PanoDreamer, a novel method for producing a coherent 360° 3D scene from a single input image. Unlike existing methods that generate the scene sequentially…
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…
TileGen: Tileable, Controllable Material Generation and Capture
Xilong Zhou, Miloš Hašan, Valentin Deschaintre +3
Recent methods (e.g. MaterialGAN) have used unconditional GANs to generate per-pixel material maps, or as a prior to reconstruct materials from input photographs. These models can…