47 citations · 66 across the 13 of their papers we have counts for
14 papers · 1 filter
PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers
Songlin Li, Despoina Paschalidou, Leonidas Guibas
The increased demand for tools that automate the 3D content creation process led to tremendous progress in deep generative models that can generate diverse 3D objects of high fidel…
MultiPhys: Multi-Person Physics-aware 3D Motion Estimation
Nicolas Ugrinovic, Boxiao Pan, Georgios Pavlakos +5
We introduce MultiPhys, a method designed for recovering multi-person motion from monocular videos. Our focus lies in capturing coherent spatial placement between pairs of individu…
CAD: Photorealistic 3D Generation via Adversarial Distillation
Ziyu Wan, Despoina Paschalidou, Ian Huang +5
The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects. Most of the…
CC3D: Layout-Conditioned Generation of Compositional 3D Scenes
Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou +4
In this work, we introduce CC3D, a conditional generative model that synthesizes complex 3D scenes conditioned on 2D semantic scene layouts, trained using single-view images. Diffe…
CurveCloudNet: Processing Point Clouds with 1D Structure
Colton Stearns, Davis Rempe, Jiateng Liu +5
Modern depth sensors such as LiDAR operate by sweeping laser-beams across the scene, resulting in a point cloud with notable 1D curve-like structures. In this work, we introduce a…
ALTO: Alternating Latent Topologies for Implicit 3D Reconstruction
Zhen Wang, Shijie Zhou, Jeong Joon Park +5
This work introduces alternating latent topologies (ALTO) for high-fidelity reconstruction of implicit 3D surfaces from noisy point clouds. Previous work identifies that the spatia…
COPILOT: Human-Environment Collision Prediction and Localization from Egocentric Videos
Boxiao Pan, Bokui Shen, Davis Rempe +4
The ability to forecast human-environment collisions from egocentric observations is vital to enable collision avoidance in applications such as VR, AR, and wearable assistive robo…
3D-Aware Video Generation
Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou +5
Generative models have emerged as an essential building block for many image synthesis and editing tasks. Recent advances in this field have also enabled high-quality 3D or video c…
ATISS: Autoregressive Transformers for Indoor Scene Synthesis
Despoina Paschalidou, Amlan Kar, Maria Shugrina +3
The ability to synthesize realistic and diverse indoor furniture layouts automatically or based on partial input, unlocks many applications, from better interactive 3D tools to dat…
Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks
Despoina Paschalidou, Angelos Katharopoulos, Andreas Geiger +1
Impressive progress in 3D shape extraction led to representations that can capture object geometries with high fidelity. In parallel, primitive-based methods seek to represent obje…
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image
Despoina Paschalidou, Luc van Gool, Andreas Geiger
Humans perceive the 3D world as a set of distinct objects that are characterized by various low-level (geometry, reflectance) and high-level (connectivity, adjacency, symmetry) pro…
Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboids
Despoina Paschalidou, Ali Osman Ulusoy, Andreas Geiger
Abstracting complex 3D shapes with parsimonious part-based representations has been a long standing goal in computer vision. This paper presents a learning-based solution to this p…
RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials
Despoina Paschalidou, Ali Osman Ulusoy, Carolin Schmitt +2
In this paper, we consider the problem of reconstructing a dense 3D model using images captured from different views. Recent methods based on convolutional neural networks (CNN) al…
PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds
Aseem Behl, Despoina Paschalidou, Simon Donné +1
Despite significant progress in image-based 3D scene flow estimation, the performance of such approaches has not yet reached the fidelity required by many applications. Simultaneou…