Open☀️3D

Introduction

For intelligent agents to thrive in the physical world, they must not only perceive but also comprehend and act within it. This year’s workshop unites leading researchers advancing world models and spatial intelligence, from 3D perception and scene understanding to generative world representations. Through keynotes and a challenge on open 3D interaction perception, we will explore how machines learn to reason about and engage with their environments. The workshop aims to shape the next generation of spatially grounded AI, bridging scientific discovery, practical deployment, and responsible innovation.

Keynote Speakers

Georgia Gkioxari

Assistant Professor at Caltech

Peter Kontschieder

Research Director at Meta

Dima Damen

University of Bristol / Google DeepMind

Matthias Nießner

TUM / Spaitial AI

Paper Track Open

Submission Type	Length	In Proceedings	Deadline	Policies
Proceedings Track	8 pages	Yes	TBD	Anonymous, subject to dual-submission rules.
Non-Archival Track	4 / 8 pages	No	TBD	Anonymous, may include previously published work.

Submit via OpenReview

All submissions must be anonymous and follow the ECCV 26 author guidelines.

Submission Deadline 1:
Proceedings Track

8-page full papers for inclusion in the CVPR workshop proceedings. Those submissions are subject to the dual submission policy, only original work not under review or published elsewhere is allowed.

Submission deadline: August 5th, 2026
Notification to authors: August 10th, 2026
Camera-ready submission: August 15th, 2026

Submission Deadline 2:
Extended Abstracts & Non-Archival Papers

4-page extended abstracts or 8-page full papers that will not be included in the proceedings. May include previously published work that the authors want to present at the workshop.

Submission deadline: TBD
Notification to authors: TBD
May include previously published work.

Challenge Track Open

We host a 3-track challenge based on the SceneFun3D benchmark and the Articulate3D dataset. The challenge focuses on fine-grained functionality, affordance, and interaction understanding in 3D indoor environments.