Our workshop will be live 8.30 - 12.30, Oct 3, @ ICCV 2023
- In-person attendance: Convention Center Paris @ WO8
- On-line attendance: https://tudelft.zoom.us/j/95792712509
Welcome to the first workshop on Computer Vision Aided Architectural Design (CVAAD). We are delighted that our workshop will be hosted at the International Conference on Computer Vision (ICCV), October 3, 2023.
About the workshop
The workshop aims at expanding the interdisciplinary domain of computer vision in architectural design, encouraging collaboration, and investigating common research interests. By showcasing datasets and applications from architectural design, this workshop creates opportunities for computer vision researchers. Through keynote talks, discussions, and a workshop challenge, attendees will explore relevant topics from both generative and analytic computer vision for the applications and processes in architectural design. This will shed light on the needs, constraints, and challenges associated with developing and implementing effective computer vision tasks and methods in architectural design and research. The workshop consists of the following:
Speakers
- Noah Snavely, Cornell Tech and Google Research
- Daniel G. Aliaga, Purdue University
- Francis Engelmann, ETH Zurich
- Matthias Strandfest, A.G. Archylise
Accepted workshop papers
- Scalable MAV Indoor Reconstruction with Neural Implicit Surfaces
- PanoStyle: Semantic, Geometry-Aware, and Shading Independent Photorealistic Style Transfer for Indoor Panoramic Scenes
- MARL: Multi-scale Archetype Representation Learning for Building Energy Estimation
- SSIG: A Visually-Guided Graph Edit Distance for Floor Plan Similarity
- Floor Plan Reconstruction from Sparse Views: Combining Graph Neural Network with Constrained Diffusion
(Links will be included later.)
Poster panel
ICCV 2023 conference papers
- Doppelgangers: Learning to Disambiguate Images of Similar Structures
- SGAligner: 3D Scene Alignment with Scene Graphs
- GlobalMapper: Arbitrary-Shaped Urban Layout Generation
- Boosting 3-DoF Ground-to-Satellite Camera Localization Accuracy via Geometry-Guided Cross-View Transformer
Guest Posters
- Carbon Image Project
- A Taxonomy of Visual Data in Architectural Design
Organization
Seyran Khademi
Assist. Prof. at the faculty of Architecture and the Built Environment, Delft University of Technology
Jan van Gemert
Assoc. Prof. at the faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology
Iro Armeni
Assist. Prof. at the department of Civil and Environmental Engineering, Stanford University
Fatemeh Mostafavi
Doctoral candidate at the faculty of Architecture and the Built Environment, Delft University of Technology
Casper van Engelenburg
Doctoral candidate at the faculty of Architecture and the Built Environment, Delft University of Technology
