5 citations · 8 across the 3 of their papers we have counts for
6 papers · 1 filter
PlaceIt3D: Language-Guided Object Placement in Real 3D Scenes
Ahmed Abdelreheem, Filippo Aleotti, Jamie Watson +6
We introduce the novel task of Language-Guided Object Placement in Real 3D Scenes. Our model is given a 3D scene's point cloud, a 3D asset, and a textual prompt broadly describing…
ZeroKey: Point-Level Reasoning and Zero-Shot 3D Keypoint Detection from Large Language Models
Bingchen Gong, Diego Gomez, Abdullah Hamdi +4
We propose a novel zero-shot approach for keypoint detection on 3D shapes. Point-level reasoning on visual data is challenging as it requires precise localization capability, posin…
3DCoMPaT: An improved Large-scale 3D Vision Dataset for Compositional Recognition
Habib Slim, Xiang Li, Yuchen Li +8
In this work, we present 3DCoMPaT, a multimodal 2D/3D dataset with 160 million rendered views of more than 10 million stylized 3D shapes carefully annotated at the part-inst…
Zero-Shot 3D Shape Correspondence
Ahmed Abdelreheem, Abdelrahman Eldesokey, Maks Ovsjanikov +1
We propose a novel zero-shot approach to computing correspondences between 3D shapes. Existing approaches mainly focus on isometric and near-isometric shape pairs (e.g., human vs.…
SATR: Zero-Shot Semantic Segmentation of 3D Shapes
Ahmed Abdelreheem, Ivan Skorokhodov, Maks Ovsjanikov +1
We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D image recognition models. Surprisingly, we find that modern zero-shot 2D o…
ScanEnts3D: Exploiting Phrase-to-3D-Object Correspondences for Improved Visio-Linguistic Models in 3D Scenes
Ahmed Abdelreheem, Kyle Olszewski, Hsin-Ying Lee +2
The two popular datasets ScanRefer [16] and ReferIt3D [3] connect natural language to real-world 3D data. In this paper, we curate a large-scale and complementary dataset extending…