Publications (13)
Fast and Explicit Neural View Synthesis
Pengsheng Guo, Miguel Angel Bautista, Alex Colburn +4
We study the problem of novel view synthesis from sparse source observations of a scene comprised of 3D objects. We propose a simple yet effective approach that is neither continuo…
Learning Stylized Character Expressions from Humans
Deepali Aneja, Alex Colburn, Gary Faigin +2
We present DeepExpr, a novel expression transfer system from humans to multiple stylized characters via deep learning. We developed : 1) a data-driven perceptual model of facial ex…
Equivariant Neural Rendering
Emilien Dupont, Miguel Angel Bautista, Alex Colburn +4
We propose a framework for learning neural scene representations directly from images, without 3D supervision. Our key insight is that 3D structure can be imposed by ensuring that…
Pseudo-Generalized Dynamic View Synthesis from a Video
Xiaoming Zhao, Alex Colburn, Fangchang Ma +3
Rendering scenes observed in a monocular video from novel viewpoints is a challenging problem. For static scenes the community has studied both scene-specific optimization techniqu…
AutoFocusFormer: Image Segmentation off the Grid
Chen Ziwen, Kaushik Patnaik, Shuangfei Zhai +5
Real world images often have highly imbalanced content density. Some areas are very uniform, e.g., large patches of blue sky, while other areas are scattered with many small object…
Generative Multiplane Images: Making a 2D GAN 3D-Aware
Xiaoming Zhao, Fangchang Ma, David Güera +3
What is really needed to make an existing 2D GAN 3D-aware? To answer this question, we modify a classical GAN, i.e., StyleGANv2, as little as possible. We find that only two modifi…
LivePose: Online 3D Reconstruction from Monocular Video with Dynamic Camera Poses
Noah Stier, Baptiste Angles, Liang Yang +3
Dense 3D reconstruction from RGB images traditionally assumes static camera pose estimates. This assumption has endured, even as recent works have increasingly focused on real-time…
Deep Neural Network Approach for Annual Luminance Simulations
Yue Liu, Alex Colburn, Mehlika Inanici
Annual luminance maps provide meaningful evaluations for occupants' visual comfort, preferences, and perception. However, acquiring long-term luminance maps require labor-intensive…
LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image
Chuhang Zou, Alex Colburn, Qi Shan +1
We propose an algorithm to predict room layout from a single image that generalizes across panoramas and perspective images, cuboid layouts and more general layouts (e.g. L-shape r…
FineRecon: Depth-aware Feed-forward Network for Detailed 3D Reconstruction
Noah Stier, Anurag Ranjan, Alex Colburn +4
Recent works on 3D reconstruction from posed images have demonstrated that direct inference of scene-level 3D geometry without test-time optimization is feasible using deep neural…
StableDreamer: Taming Noisy Score Distillation Sampling for Text-to-3D
Pengsheng Guo, Hans Hao, Adam Caccavale +7
In the realm of text-to-3D generation, utilizing 2D diffusion models through score distillation sampling (SDS) frequently leads to issues such as blurred appearances and multi-face…
BADGR: Bundle Adjustment Diffusion Conditioned by GRadients for Wide-Baseline Floor Plan Reconstruction
Yuguang Li, Ivaylo Boyadzhiev, Zixuan Liu +2
Reconstructing precise camera poses and floor plan layouts from wide-baseline RGB panoramas is a difficult and unsolved problem. We introduce BADGR, a novel diffusion model that jo…
Manhattan Room Layout Reconstruction from a Single 360 image: A Comparative Study of State-of-the-art Methods
Chuhang Zou, Jheng-Wei Su, Chi-Han Peng +5
Recent approaches for predicting layouts from 360 panoramas produce excellent results. These approaches build on a common framework consisting of three steps: a pre-processing step…