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Found 10 papers, 3 papers with code
VIBES -- Vision Backbone Efficient Selection
This work tackles the challenge of efficiently selecting high-performance pre-trained vision backbones for specific target tasks.
Benchmarking person re-identification datasets and approaches for practical real-world implementations
Recently, Person Re-Identification (Re-ID) has received a lot of attention.
TrADe Re-ID -- Live Person Re-Identification using Tracking and Anomaly Detection
The initial live Re-ID baseline used a pedestrian detector to build a large search gallery and a classic Re-ID model to find the query in the gallery.
Unifying Evaluation of Machine Learning Safety Monitors
This paper introduces three unified safety-oriented metrics, representing the safety benefits of the monitor (Safety Gain), the remaining safety gaps after using it (Residual Hazard), and its negative impact on the system's performance (Availability Cost).
Evaluation of Runtime Monitoring for UAV Emergency Landing
The first contribution of this paper is to present a new EL approach, in line with safety requirements introduced in recent research.
Benchmarking person re-identification approaches and training datasets for practical real-world implementations
Person Re-Identification (Re-ID) is receiving a lot of attention recently.
Certifying Emergency Landing for Safe Urban UAV
Unmanned Aerial Vehicles (UAVs) have the potential to be used for many applications in urban environments.
Combining pretrained CNN feature extractors to enhance clustering of complex natural images
First, extensive experiments are conducted and show that, for a given dataset, the choice of the CNN architecture for feature extraction has a huge impact on the final clustering.
Robust Detection of Objects under Periodic Motion with Gaussian Process Filtering
Object Detection (OD) is an important task in Computer Vision with many practical applications.
Learning local trajectories for high precision robotic tasks : application to KUKA LBR iiwa Cartesian positioning
By exploration and regression, linear and quadratic models are learnt for respectively the dynamics and cost function.
