19 citations · 55 across the 15 of their papers we have counts for
4 papers · 1 filter
Video Test-Time Adaptation for Action Recognition
Wei Lin, Muhammad Jehanzeb Mirza, Mateusz Kozinski +3
Although action recognition systems can achieve top performance when evaluated on in-distribution test points, they are vulnerable to unanticipated distribution shifts in test data…
ActMAD: Activation Matching to Align Distributions for Test-Time-Training
Muhammad Jehanzeb Mirza, Pol Jané Soneira, Wei Lin +3
Test-Time-Training (TTT) is an approach to cope with out-of-distribution (OOD) data by adapting a trained model to distribution shifts occurring at test-time. We propose to perform…
MATE: Masked Autoencoders are Online 3D Test-Time Learners
M. Jehanzeb Mirza, Inkyu Shin, Wei Lin +8
Our MATE is the first Test-Time-Training (TTT) method designed for 3D data, which makes deep networks trained for point cloud classification robust to distribution shifts occurring…
Enforcing connectivity of 3D linear structures using their 2D projections
Doruk Oner, Hussein Osman, Mateusz Kozinski +1
Many biological and medical tasks require the delineation of 3D curvilinear structures such as blood vessels and neurites from image volumes. This is typically done using neural ne…