arXiv Machine Learning
EMERGE: Resolution-Agnostic Point Cloud Generation with Equivariant Graph-Based Diffusion
Read the original on arXiv Machine Learning →The Flow has not summarised this story yet — read it at arXiv Machine Learning.
Related stories
arXiv Computer Vision
4d ago
Point Diffusion Mamba: Unified Diffusion-State-Space Modeling for Single-View 3D Reconstruction under Data Scarcity
Point Diffusion Mamba (PDM) is a new method that fuses diffusion models with state‑space modeling to perform single‑view 3D reconstruction when training data are scarce. It uses a lightweight reconstruction module for unordered point‑clouds, a Local Geometric Aggregation module combined with Mamba blocks to capture both global geometry and local detail, and a Hierarchical Feature Integration Network to merge high‑level semantic and local geometric features for each point. A Dynamic Weighted Sampling strategy further improves reconstruction quality by integrating generative priors, and experiments on ShapeNet and Pix3D show that PDM outperforms existing state‑of‑the‑art approaches.
arXiv Computer Vision
Sep 10
GTA: Advancing Image-to-3D World Generation via Geometry Then Appearance Video Diffusion
arXiv:2605.12957v2 Announce Type: replace Abstract: Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of do...
arXiv Computer Vision
5d ago
ScaleBlind: Point Cloud Completion under Unknown Scale
arXiv:2609.23404v1 Announce Type: new Abstract: Point cloud completion aims to infer a complete 3D shape from a partial point cloud and serves as a fundamental building block for downstream tasks suc...
arXiv Computer Vision
Sep 15
Mind2Cloud: EEG-to-Point Cloud Generation with Two-Granularity Diffusion Decoding
arXiv:2609.13991v1 Announce Type: new Abstract: Reconstructing 3D objects from brain signals offers a promising avenue for understanding human visual cognition. While prior work has shown initial suc...
arXiv Machine Learning
Sep 1
Generation of High-Level Concepts in 3D Scene Graphs via Autoregressive Diffusion
arXiv:2608.28733v1 Announce Type: cross Abstract: Indoor 3D Scene Graphs (3DSGs) represent environments as multi-layer hierarchies that connect observed geometric primitives (e.g., planes) to higher-...
arXiv Computer Vision
2d ago
M3GD: Multi-Modal Multi-View Geometric Diffusion for Camera--LiDAR Novel View Synthesis
arXiv:2609.30056v1 Announce Type: cross Abstract: Robotic novel view synthesis (NVS) must recover both visual appearance and metric 3D structure, yet most generative NVS methods rely only on images,...