4 citations · 12 across the 8 of their papers we have counts for
6 papers · 1 filter
Linkify: Learning from Interface-Augmented Assembly Graphs
Anushrut Jignasu, Daniele Grandi
We present Linkify, a framework for learning from interface-augmented assembly graphs to enable context-aware part retrieval in mechanical assemblies. While recent generative AI me…
Decorum: A Language-Based Approach For Style-Conditioned Synthesis of Indoor 3D Scenes
Kelly O. Marshall, Omid Poursaeed, Sergiu Oprea +5
3D indoor scene generation is an important problem for the design of digital and real-world environments. To automate this process, a scene generation model should be able to not o…
STITCH: Surface reconstrucTion using Implicit neural representations with Topology Constraints and persistent Homology
Anushrut Jignasu, Ethan Herron, Zhanhong Jiang +5
We present STITCH, a novel approach for neural implicit surface reconstruction of a sparse and irregularly spaced point cloud while enforcing topological constraints (such as havin…
Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing
Anushrut Jignasu, Kelly O. Marshall, Ankush Kumar Mishra +5
G-code (Geometric code) or RS-274 is the most widely used computer numerical control (CNC) and 3D printing programming language. G-code provides machine instructions for the moveme…
Evaluating Neural Radiance Fields (NeRFs) for 3D Plant Geometry Reconstruction in Field Conditions
Muhammad Arbab Arshad, Talukder Jubery, James Afful +5
We evaluate different Neural Radiance Fields (NeRFs) techniques for the 3D reconstruction of plants in varied environments, from indoor settings to outdoor fields. Traditional meth…
ZeroForge: Feedforward Text-to-Shape Without 3D Supervision
Kelly O. Marshall, Minh Pham, Ameya Joshi +4
Current state-of-the-art methods for text-to-shape generation either require supervised training using a labeled dataset of pre-defined 3D shapes, or perform expensive inference-ti…