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Home/Authors/Jun Gao

Jun Gao

Topic trends: 31,945 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,180 papers | Abstracts: 30,898 (90.4%) | Citations: 34,180 (100.0%) | arXiv: 25,729 (75.3%)

Built: Feb 6, 2026, 2:31 PM AMS

19

papers

262

total citations

papers (19)

GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control

DIFIX3D+: Improving 3D Reconstructions with Single-Step Diffusion Models

PartField: Learning 3D Feature Fields for Part Segmentation and Beyond

Interleaved-Modal Chain-of-Thought

Diffusion Renderer: Neural Inverse and Forward Rendering with Video Diffusion Models

InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models

AIM: Let Any Multimodal Large Language Models Embrace Efficient In-Context Learning

DatasetGAN: Efficient Labeled Data Factory With Minimal Human Effort

Extracting Triangular 3D Models, Materials, and Lighting From Images

Magic3D: High-Resolution Text-to-3D Content Creation

Neural Fields Meet Explicit Geometric Representations for Inverse Rendering of Urban Scenes

3DStyleNet: Creating 3D Shapes With Geometric and Texture Style Variations

Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid

ScribbleBox: Interactive Annotation Framework for Video Object Segmentation

Interactive Annotation of 3D Object Geometry using 2D Scribbles

Learning Deformable Tetrahedral Meshes for 3D Reconstruction

NeurIPS 2020arXiv

Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis

NeurIPS 2021arXiv

DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer

NeurIPS 2021arXiv

GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images

NeurIPS 2022arXiv