37 citations · 101 across the 57 of their papers we have counts for
60 papers · 1 filter
3DHarnessBench: Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models
Ling Liu, Bingchen Gong, Amal Dev Parakkat +1
We introduce 3DHarnessBench, a benchmark that evaluates the agentic ability of frontier vision-language models (VLMs) to recover 3D geometry as Blender Python code from a variety o…
SeeSE3: Emergence of 3D Space in Vision Features
Caroline Chen, Sayna Ebrahimi, Fedor Kitashov +4
In this paper, we ask whether vision foundation models construct representations that reflect the intrinsic properties of 3D Euclidean space. Unlike previous works that probe 3D aw…
Gen4U: Unifying Video Generation and Understanding via Diffusion
Michael King, Aravindh Mahendran, Matthew Koichi Grimes +5
Prior work suggests that diffusion representations capture low-level geometry but struggle with high-level semantics. We demonstrate that state-of-the-art video diffusion models ov…
FILTR: Extracting Topological Features from Pretrained 3D Models
Louis Martinez, Maks Ovsjanikov
Recent advances in pretraining 3D point cloud encoders (e.g., Point-BERT, Point-MAE) have produced powerful models, whose abilities are typically evaluated on geometric or semantic…
From Blobs to Spokes: High-Fidelity Surface Reconstruction via Oriented Gaussians
Diego Gomez, Antoine Guédon, Nissim Maruani +2
3D Gaussian Splatting (3DGS) has revolutionized fast novel view synthesis, yet its opacity-based formulation makes surface extraction fundamentally difficult. Unlike implicit metho…
Beyond Prompts: Unconditional 3D Inversion for Out-of-Distribution Shapes
Victoria Yue Chen, Emery Pierson, Léopold Maillard +1
Text-driven inversion of generative models is a core paradigm for manipulating 2D or 3D content, unlocking numerous applications such as text-based editing, style transfer, or inve…