AIMC Topic: Pedestrians

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Self-Training With Progressive Representation Enhancement for Unsupervised Cross-Domain Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In recent years, person re-identification (re-ID) has achieved relatively good performance, benefiting from the revival of deep neural networks. However, due to the existence of domain bias which refers to the different data distributions between two...

Pedestrian attribute recognition using two-branch trainable Gabor wavelets network.

PloS one
Keeping an eye on pedestrians as they navigate through a scene, surveillance cameras are everywhere. With this context, our paper addresses the problem of pedestrian attribute recognition (PAR). This problem entails recognizing attributes such as age...

Designing Interpretable Recurrent Neural Networks for Video Reconstruction via Deep Unfolding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Deep unfolding methods design deep neural networks as learned variations of optimization algorithms through the unrolling of their iterations. These networks have been shown to achieve faster convergence and higher accuracy than the original optimiza...

Mask-Guided Attention Network and Occlusion-Sensitive Hard Example Mining for Occluded Pedestrian Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Pedestrian detection relying on deep convolution neural networks has made significant progress. Though promising results have been achieved on standard pedestrians, the performance on heavily occluded pedestrians remains far from satisfactory. The ma...

Person Reidentification via Unsupervised Cross-View Metric Learning.

IEEE transactions on cybernetics
Person reidentification (Re-ID) aims to match observations of individuals across multiple nonoverlapping camera views. Recently, metric learning-based methods have played important roles in addressing this task. However, metrics are mostly learned in...

Batch Coherence-Driven Network for Part-Aware Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Existing part-aware person re-identification methods typically employ two separate steps: namely, body part detection and part-level feature extraction. However, part detection introduces an additional computational cost and is inherently challenging...

Locomotion with Pedestrian Aware from Perception Sensor by Pavement Sweeping Reconfigurable Robot.

Sensors (Basel, Switzerland)
Regular washing of public pavements is necessary to ensure that the public environment is sanitary for social activities. This is a challenge for autonomous cleaning robots, as they must adapt to the environment with varying pavement widths while avo...

Holistic LSTM for Pedestrian Trajectory Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Accurate predictions of future pedestrian trajectory could prevent a considerable number of traffic injuries and improve pedestrian safety. It involves multiple sources of information and real-time interactions, e.g., vehicle speed and ego-motion, pe...

Multi-View Gait Image Generation for Cross-View Gait Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Gait recognition aims to recognize persons' identities by walking styles. Gait recognition has unique advantages due to its characteristics of non-contact and long-distance compared with face and fingerprint recognition. Cross-view gait recognition i...

Complementary Pseudo Labels for Unsupervised Domain Adaptation On Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In recent years, supervised person re-identification (re-ID) models have received increasing studies. However, these models trained on the source domain always suffer dramatic performance drop when tested on an unseen domain. Existing methods are pri...