Andreas Geiger

54

Papers

258

Total Citations

Papers (54)

Generalized Predictive Model for Autonomous Driving

GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers

Artificial Kuramoto Oscillatory Neurons

SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic

Prometheus: 3D-Aware Latent Diffusion Models for Feed-Forward Text-to-3D Scene Generation

GenFusion: Closing the Loop between Reconstruction and Generation via Videos

EVolSplat: Efficient Volume-based Gaussian Splatting for Urban View Synthesis

LoftUp: Learning a Coordinate-Based Feature Upsampler for Vision Foundation Models

UrbanCAD: Towards Highly Controllable and Photorealistic 3D Vehicles for Urban Scene Simulation

MoGA: 3D Generative Avatar Prior for Monocular Gaussian Avatar Reconstruction

DepthSplat: Connecting Gaussian Splatting and Depth

Volumetric Surfaces: Representing Fuzzy Geometries with Layered Meshes

Easi3R: Estimating Disentangled Motion from DUSt3R Without Training

GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs

MuRF: Multi-Baseline Radiance Fields

NeLF-Pro: Neural Light Field Probes for Multi-Scale Novel View Synthesis

Mip-Splatting: Alias-free 3D Gaussian Splatting

3DGS-Avatar: Animatable Avatars via Deformable 3D Gaussian Splatting

HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting

IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing

On Joint Estimation of Pose, Geometry and svBRDF From a Handheld Scanner

Learning Unsupervised Hierarchical Part Decomposition of 3D Objects From a Single RGB Image

Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D Supervision

Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis

Exploring Data Aggregation in Policy Learning for Vision-Based Urban Autonomous Driving

Learning Situational Driving

GIRAFFE: Representing Scenes As Compositional Generative Neural Feature Fields

Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration

SMD-Nets: Stereo Mixture Density Networks

Neural Parts: Learning Expressive 3D Shape Abstractions With Invertible Neural Networks

PINA: Learning a Personalized Implicit Neural Avatar From a Single RGB-D Video Sequence

gDNA: Towards Generative Detailed Neural Avatars

RegNeRF: Regularizing Neural Radiance Fields for View Synthesis From Sparse Inputs

NEAT: Neural Attention Fields for End-to-End Autonomous Driving

SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes

KiloNeRF: Speeding Up Neural Radiance Fields With Thousands of Tiny MLPs

UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction

SLIM: Self-Supervised LiDAR Scene Flow and Motion Segmentation

AG3D: Learning to Generate 3D Avatars from 2D Image Collections

Hidden Biases of End-to-End Driving Models

Convolutional Occupancy Networks

Category Level Object Pose Estimation via Neural Analysis-by-Synthesis

ARAH: Animatable Volume Rendering of Articulated Human SDFs

TensoRF: Tensorial Radiance Fields

KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients

GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis

NeurIPS 2020arXiv

MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images

NeurIPS 2021arXiv

ATISS: Autoregressive Transformers for Indoor Scene Synthesis

NeurIPS 2021arXiv

Shape As Points: A Differentiable Poisson Solver

NeurIPS 2021arXiv

Projected GANs Converge Faster

NeurIPS 2021arXiv

On the Frequency Bias of Generative Models

NeurIPS 2021arXiv

MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction

NeurIPS 2022arXiv

VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids

NeurIPS 2022arXiv