Search Results for author:
Found 9 papers, 2 papers with code
FIR-based Future Trajectory Prediction in Nighttime Autonomous Driving
In order to minimize false collision warnings, in our multi-step framework, first, the large animal is accurately detected and a preliminary risk level is predicted for it and low-risk animals are discarded.
Using simulation to quantify the performance of automotive perception systems
The simulation can be used to characterize system performance or to test its performance under conditions that are difficult to measure (e. g., nighttime for automotive perception systems).
Context Aware Road-user Importance Estimation (iCARE)
In this paper, we propose a novel architecture for road-user importance estimation which takes advantage of the local and global context of the scene.
advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns
The results demonstrate that deep re-ID systems are vulnerable to our physical attacks.
Attention-based Few-Shot Person Re-identification Using Meta Learning
In this paper, we investigate the challenging task of person re-identification from a new perspective and propose an end-to-end attention-based architecture for few-shot re-identification through meta-learning.
Person Re-identification Using Visual Attention
Despite recent attempts for solving the person re-identification problem, it remains a challenging task since a person's appearance can vary significantly when large variations in view angle, human pose, and illumination are involved.
Multi-View Task-Driven Recognition in Visual Sensor Networks
Nowadays, distributed smart cameras are deployed for a wide set of tasks in several application scenarios, ranging from object recognition, image retrieval, and forensic applications.
End-to-end Binary Representation Learning via Direct Binary Embedding
Furthermore, in the effort of handling multilabel images, we design a joint cross entropy loss that includes both softmax cross entropy and weighted binary cross entropy in consideration of the correlation and independence of labels, respectively.
Feature Encoding in Band-limited Distributed Surveillance Systems
Distributed surveillance systems have become popular in recent years due to security concerns.
