1 code implementation • NeurIPS 2023 • Miltiadis Kofinas, Erik J. Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves
Systems of interacting objects often evolve under the influence of field effects that govern their dynamics, yet previous works have abstracted away from such effects, and assume that systems evolve in a vacuum.
1 code implementation • NeurIPS 2021 • Miltiadis Kofinas, Naveen Shankar Nagaraja, Efstratios Gavves
Modelling interactions is critical in learning complex dynamical systems, namely systems of interacting objects with highly non-linear and time-dependent behaviour.
no code implementations • 14 Mar 2021 • Manoj Rohit Vemparala, Alexander Frickenstein, Nael Fasfous, Lukas Frickenstein, Qi Zhao, Sabine Kuhn, Daniel Ehrhardt, Yuankai Wu, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele
The distilled models exhibit their strength against all white box attacks with an exception of C&W.
no code implementations • 15 Jun 2020 • Alexander Frickenstein, Manoj Rohit Vemparala, Jakob Mayr, Naveen Shankar Nagaraja, Christian Unger, Federico Tombari, Walter Stechele
The driveable area detection, posed as a two class segmentation task, can be efficiently modeled with slim binary networks.
no code implementations • 15 Oct 2019 • Tessa van der Heiden, Naveen Shankar Nagaraja, Christian Weiss, Efstratios Gavves
The Critic network is environmentally aware to prune trajectories that are in collision or are in violation with the environment.
no code implementations • 4 Mar 2019 • Oliver Scheel, Naveen Shankar Nagaraja, Loren Schwarz, Nassir Navab, Federico Tombari
Lane change prediction of surrounding vehicles is a key building block of path planning.
no code implementations • ICCV 2015 • Naveen Shankar Nagaraja, Frank R. Schmidt, Thomas Brox
As the use of videos is becoming more popular in computer vision, the need for annotated video datasets increases.