Lecture
Visual Recognition: Integrated 3D + Semantics
Description
This lecture covers topics related to visual recognition, including feedforward vs feedback models, image level labeling, scene graphs, and 3D scene graph integration. It also discusses the use of neural networks in recognition pipelines and embodied vision. The instructor presents various datasets and challenges in the field, as well as cognitive maps in rats and men.
This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.
Watch on MediaspaceOfficial source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related lectures (39)
Vision-Language-Action Models: Training and Applications
Delves into training and applications of Vision-Language-Action models, emphasizing large language models' role in robotic control and the transfer of web knowledge. Results from experiments and future research directions are highlighted.
Improving Models of the Ventral Visual Pathway
Explores computational models of the ventral visual system, focusing on optimizing networks for real-world tasks and comparing to brain data.
Vectorworks Educational Version
Introduces Vectorworks Educational Version for architectural drawings, covering tools, layers, and annotations.
Deep Visual Recognition: Interpretability
Explores deep visual recognition, interpretability, CNN architectures, visual dictionaries, and attention mechanisms.
Turbulence: Numerical Flow Simulation
Explores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.