2nd Workshop on Traditional Computer Vision in the Age of Deep Learning (TradiCV)

We invite submissions describing high-quality, well-documented, reproducible and original research. All submissions have to be through CMT in the ECCV'24 paper format. The submissions will undergo a thorough double-blind peer-review process. Topics of interest at TradiCV include but are not limited to:

• Computer vision theory

• Analytical and closed-form approaches

• Minimal problems

• Camera calibration and structure-from-motion

• Optimization techniques for computer vision

• Probabilistic approaches

• Parametric and morphable models

• Physics-based computer vision formulations

• Neuroexplicit models in computer vision

• Unsupervised/Self-supervised learning in vision

• Resource-efficient computer vision techniques

• Methods relying on computer graphics (e.g. image-based, inverse, and neural rendering)

• Surveys, case studies, and evaluation reports (considering such aspects as data efficiency, power consumption, ethical considerations, and others)

CMT webpage:
https://cmt3.research.microsoft.com/TRADICV2024

Important Dates

Paper submission deadline: July 12, 2024 (23:59:59 PDT) 

Notification of acceptance: August 2, 2024