Many state-of-the-art solutions for vehicle re- identification (re-id) mostly focus on improving the accuracy on existing re-id benchmarks using additional.
We propose a simple yet effective hybrid solution empowered by self-supervised learning which is free of intricate and computationally-demanding add-on ...
May 16, 2022 · We propose a simple yet effective hybrid solution empowered by self-supervised training which only uses a single network during inference time.
Therefore, we present SSBVER, a hybrid learning approach that employs the power of self-supervision to boost vehicle re-id perfor- mance while preserving the ...
Through extensive experiments, we show our approach, termed Self-Supervised and Boosted VEhicle Re-Identification (SSBVER), is on par with state-of-the-art ...
We propose a simple yet effective hybrid solution empowered by self-supervised learning which is free of intricate and computationally-demanding add-on ...
The code for training and testing of Robust and Scalable Vehicle Re-Identification via Self-Supervision (SSBVER) on VeRi, VehicleID and VeRiWild datasets.
Robust and scalable vehicle re-identification via self-supervision. P Khorramshahi, V Shenoy, R Chellappa. Proceedings of the IEEE/CVF Conference on Computer ...
Self-Supervised Geometric Features Discovery via Interpretable Attention for Vehicle Re-Identification and Beyond (ICCV) pdf. 2020. VehicleNet: Learning Robust ...
Missing: Scalable | Show results with:Scalable
This work proposes a simple yet effective hybrid solution empowered by self-supervised learning which is free of intricate and computationally-demanding ...