POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images - EXAKI training

EXAKI training number 1. In this session, we present a joint work produced in collaboration between CIIRC at CTU in Prague and valeo.ai within the EXA4MIND project.This work focuses on leveraging multimodal learning, particularly language-vision integration, to enable open-vocabulary 3D scene understanding. This is based on our work called “POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images”, which was presented at NeurIPS.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-11
DOI
https://doi.org/10.5281/zenodo.15861854
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images - EXAKI training

Zenodo (CERN European Organization for Nuclear Research)
Multimodal Machine Learning Applications
article

POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images - EXAKI training

article en

Abstract

EXAKI training number 1. In this session, we present a joint work produced in collaboration between CIIRC at CTU in Prague and valeo.ai within the EXA4MIND project.This work focuses on leveraging multimodal learning, particularly language-vision integration, to enable open-vocabulary 3D scene understanding. This is based on our work called “POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images”, which was presented at NeurIPS.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 56%
Multimodal Machine Learning Applications
DOIOpen Access PDFOpenAlex
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POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images - EXAKI training · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS