GATOR: Generative and Agentic 3D Object Reconstruction From Casual Images

arXiv:2610.11215 · cs.CV, cs.RO · Submitted 2026-10-08 · Read on arXiv

cs.CV, cs.RO

Submitted: 2026-10-08

Updated: 2026-10-08

Project page: https://research.nvidia.com/labs/lpr/gator/ABSTRACT

Terminology

• Conference on Computer Vision and Pattern Recognition — 15× in this paper
• Generative Model — 12× in this paper · explained in 2 episodes
• Alignment — 10× in this paper · explained in 1 episode
• Ablation — 6× in this paper · explained in 1 episode
• Fidelity — 6× in this paper · explained in 2 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• In European Conference on Computer Vision — 4× in this paper
• Consistency — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Agentic Framework — 2× in this paper · explained in 6 episodes
• CVF International Conference on Computer Vision — 2× in this paper
• Calibration — 2× in this paper · explained in 7 episodes
• Digital Twin — 2× in this paper · explained in 5 episodes
• Verification — 2× in this paper · explained in 2 episodes
• alpha — 2× in this paper · explained in 1 episode
• 6D Object Pose Estimation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Decode — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes

Sources

• HANDAL: A Dataset of Real-World Manipulable Object Categories with Pose Annotations, Affordances, and Reconstructions
• UniRecGen: Unifying Multi-View 3D Reconstruction and Generation
• ASV3D: Adapting Diffusion-Based Single-View 3D Reconstruction with Extra Imagery
• HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects
• MolmoSpaces: A Large-Scale Open Ecosystem for Robot Navigation and Manipulation
• MV-SAM3D: Adaptive Multi-View Fusion for Layout-Aware 3D Generation
• SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes
• UMI3D: Robust 3D Generation on Unconstrained Multi-Image Inputs via Simultaneous Focus Cross-Attention Routing
• FlowObject: Flow Steering for Bridging Generative Priors and Reconstruction Fidelity
• Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Bias
• TripoSR: Fast 3D Object Reconstruction from a Single Image
• SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
• GRUtopia: Dream General Robots in a City at Scale
• MeshLRM: Large Reconstruction Model for High-Quality Meshes
• T5Gemma 2: Seeing, Reading, and Understanding Longer
• World Tracing: Generative Pixel-Aligned Geometry Beyond the Visible
• The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
• TexVerse: A Universe of 3D Objects with High-Resolution Textures
• InternScenes: A Large-scale Simulatable Indoor Scene Dataset with Realistic Layouts
• Articraft: An Agentic System for Scalable Articulated 3D Asset Generation

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