526 citations · 1.4k across the 51 of their papers we have counts for
12 papers · 1 filter
Panoptic Lifting for 3D Scene Understanding with Neural Fields
Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Buló +4
We propose Panoptic Lifting, a novel approach for learning panoptic 3D volumetric representations from images of in-the-wild scenes. Once trained, our model can render color images…
ObjectMatch: Robust Registration using Canonical Object Correspondences
Can Gümeli, Angela Dai, Matthias Nießner
We present ObjectMatch, a semantic and object-centric camera pose estimator for RGB-D SLAM pipelines. Modern camera pose estimators rely on direct correspondences of overlapping re…
ClipFace: Text-guided Editing of Textured 3D Morphable Models
Shivangi Aneja, Justus Thies, Angela Dai +1
We propose ClipFace, a novel self-supervised approach for text-guided editing of textured 3D morphable model of faces. Specifically, we employ user-friendly language prompts to ena…
Neural Poisson: Indicator Functions for Neural Fields
Angela Dai, Matthias Nießner
Implicit neural field generating signed distance field representations (SDFs) of 3D shapes have shown remarkable progress in 3D shape reconstruction and generation. We introduce a…
Learning 3D Scene Priors with 2D Supervision
Yinyu Nie, Angela Dai, Xiaoguang Han +1
Holistic 3D scene understanding entails estimation of both layout configuration and object geometry in a 3D environment. Recent works have shown advances in 3D scene estimation fro…
FutureHuman3D: Forecasting Complex Long-Term 3D Human Behavior from Video Observations
Christian Diller, Thomas Funkhouser, Angela Dai
We present a generative approach to forecast long-term future human behavior in 3D, requiring only weak supervision from readily available 2D human action data. This is a fundament…
PatchComplete: Learning Multi-Resolution Patch Priors for 3D Shape Completion on Unseen Categories
Yuchen Rao, Yinyu Nie, Angela Dai
While 3D shape representations enable powerful reasoning in many visual and perception applications, learning 3D shape priors tends to be constrained to the specific categories tra…
Texturify: Generating Textures on 3D Shape Surfaces
Yawar Siddiqui, Justus Thies, Fangchang Ma +3
Texture cues on 3D objects are key to compelling visual representations, with the possibility to create high visual fidelity with inherent spatial consistency across different view…
Language-Grounded Indoor 3D Semantic Segmentation in the Wild
David Rozenberszki, Or Litany, Angela Dai
Recent advances in 3D semantic segmentation with deep neural networks have shown remarkable success, with rapid performance increase on available datasets. However, current 3D sema…
Weakly-Supervised End-to-End CAD Retrieval to Scan Objects
Tim Beyer, Angela Dai
CAD model retrieval to real-world scene observations has shown strong promise as a basis for 3D perception of objects and a clean, lightweight mesh-based scene representation; howe…
Neural Part Priors: Learning to Optimize Part-Based Object Completion in RGB-D Scans
Alexey Bokhovkin, Angela Dai
3D object recognition has seen significant advances in recent years, showing impressive performance on real-world 3D scan benchmarks, but lacking in object part reasoning, which is…
SPAMs: Structured Implicit Parametric Models
Pablo Palafox, Nikolaos Sarafianos, Tony Tung +1
Parametric 3D models have formed a fundamental role in modeling deformable objects, such as human bodies, faces, and hands; however, the construction of such parametric models requ…