Shenlong Wang

38

Papers

304

Total Citations

Papers (38)

PhysGen: Rigid-Body Physics-Grounded Image-to-Video Generation

GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-Mesh

PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videos

Physical Property Understanding from Language-Embedded Feature Fields

PhysGen3D: Crafting a Miniature Interactive World from a Single Image

SuperGaussian: Repurposing Video Models for 3D Super Resolution

Uni4D: Unifying Visual Foundation Models for 4D Modeling from a Single Video

DRAWER: Digital Reconstruction and Articulation With Environment Realism

LIFe-GoM: Generalizable Human Rendering with Learned Iterative Feedback Over Multi-Resolution Gaussians-on-Mesh

Demeter: A Parametric Model of Crop Plant Morphology from the Real World

IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range Images

VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction

InvRGB+L: Inverse Rendering of Complex Scenes with Unified Color and LiDAR Reflectance Modeling

Controllable Weather Synthesis and Removal with Video Diffusion Models

AD-GS: Object-Aware B-Spline Gaussian Splatting for Self-Supervised Autonomous Driving

NoPo-Avatar: Generalizable and Animatable Avatars from Sparse Inputs without Human Poses

NeurIPS 2025arXiv

Ada: A Distributed, Power-Aware, Real-Time Scene Provider for XR

Video2Game: Real-time Interactive Realistic and Browser-Compatible Environment from a Single Video

OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression

LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World

SceneGen: Learning To Generate Realistic Traffic Scenes

S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling

GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Driving

NeurMiPs: Neural Mixture of Planar Experts for View Synthesis

Virtual Correspondence: Humans as a Cue for Extreme-View Geometry

Building Rearticulable Models for Arbitrary 3D Objects From 4D Point Clouds

ContactGen: Generative Contact Modeling for Grasp Generation

PEANUT: Predicting and Navigating to Unseen Targets

ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field

MapPrior: Bird's-Eye View Map Layout Estimation with Generative Models

Deep Feedback Inverse Problem Solver

Conditional Entropy Coding for Efficient Video Compression

DSDNet: Deep Structured self-Driving Network

Learning to Generate Realistic LiDAR Point Clouds

MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models

NeurIPS 2020arXiv

SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping

CASA: Category-agnostic Skeletal Animal Reconstruction

NeurIPS 2022arXiv

Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects

NeurIPS 2023arXiv