Attendees are seated in a spacious conference hall, attentively watching a presentation at CVPR (Conference on Computer Vision and Pattern Recognition) in Seattle. The large venue features an industrial, open ceiling with visible beams and lighting fixtures. Two large projection screens at the front display slides, one of which highlights a topic titled "Gromov-Wasserstein for Encoding Structural Priors" discussing a general formulation for discrete GW problems. The audience appears focused, with some individuals taking notes. The setting suggests an engaging academic or professional session, complete with high-tech equipment and organized seating.
Text transcribed from the image:
mov-Wasserstein for
Oding Structural Priors
vely) general formulation for (discrete) GW problems
CVPR
JUNE 17-21, 2024
SEATTLE, W
Gromov-Wasserstein for
Encoding Structural Priors
A (relatively) general formulation for (discrete) GW problems:
Gromov-Wasserstein for
Encoding Structural Priors
A (relatively) general formulation for (discrete) GW problem-
Hege and phen David Tempty Content Unbalanced Optimal Transport for Upervises