7 citations · 12 across the 24 of their papers we have counts for
4 papers · 1 filter
Test-time adversarial detection and robustness for localizing humans using ultra wide band channel impulse responses
Abhiram Kolli, Muhammad Jehanzeb Mirza, Horst Possegger +1
Keyless entry systems in cars are adopting neural networks for localizing its operators. Using test-time adversarial defences equip such systems with the ability to defend against…
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…