GenIA: Generative Reconstruction with Test-Time Input Alignment

arXiv:2610.12388 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Project page: https://facebookresearch.github.io/GenIA

Terminology

• Computer Vision and Pattern Recognition — 18× in this paper
• Ablation — 14× in this paper · explained in 1 episode
• Alignment — 9× in this paper · explained in 1 episode
• Gaussian Splatting — 9× in this paper · explained in 4 episodes
• Consistency — 8× in this paper · explained in 3 episodes
• Foundation Model — 8× in this paper · explained in 3 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Foundation Models — 4× in this paper · explained in 7 episodes
• 3D Gaussian Splatting — 3× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Grounding — 3× in this paper · explained in 3 episodes
• Pattern Analysis and Machine Intelligence — 3× in this paper
• Temporal consistency — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Gradient Flow — 2× in this paper · explained in 2 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Rectified Flow — 2× in this paper · explained in 3 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space
• A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA
• MV-SAM3D: Adaptive Multi-View Fusion for Layout-Aware 3D Generation
• Learn2Splat: Extending the Horizon of Learned 3DGS Optimization
• Fast 4D Mesh Generation by Spatio-Temporal Attention Chains
• DRoPS: Dynamic 3D Reconstruction of Pre-Scanned Objects
• InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models
• 4D Gaussian Splatting: Modeling Dynamic Scenes with Native 4D Primitives
• Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

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