Multimedia big data analytics: A survey
With the proliferation of online services and mobile technologies, the world has stepped into
a multimedia big data era. A vast amount of research work has been done in the multimedia …
a multimedia big data era. A vast amount of research work has been done in the multimedia …
Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives
In the study of image and vision computing, the generalization capability of an algorithm
often determines whether it is able to work well in complex scenes. The goal of this review …
often determines whether it is able to work well in complex scenes. The goal of this review …
Collaborative and adversarial network for unsupervised domain adaptation
In this paper, we propose a new unsupervised domain adaptation approach called
Collaborative and Adversarial Network (CAN) through domain-collaborative and domain …
Collaborative and Adversarial Network (CAN) through domain-collaborative and domain …
Cross-scene crowd counting via deep convolutional neural networks
Cross-scene crowd counting is a challenging task where no laborious data annotation is
required for counting people in new target surveillance crowd scenes unseen in the training …
required for counting people in new target surveillance crowd scenes unseen in the training …
Autodial: Automatic domain alignment layers
Classifiers trained on given databases perform poorly when tested on data acquired in
different settings. This is explained in domain adaptation through a shift among distributions …
different settings. This is explained in domain adaptation through a shift among distributions …
Deepid-net: Deformable deep convolutional neural networks for object detection
In this paper, we propose deformable deep convolutional neural networks for generic object
detection. This new deep learning object detection diagram has innovations in multiple …
detection. This new deep learning object detection diagram has innovations in multiple …
Learning to count with cnn boosting
E Walach, L Wolf - Computer Vision–ECCV 2016: 14th European …, 2016 - Springer
In this paper, we address the task of object counting in images. We follow modern learning
approaches in which a density map is estimated directly from the input image. We employ …
approaches in which a density map is estimated directly from the input image. We employ …
Learning cross-modal deep representations for robust pedestrian detection
This paper presents a novel method for detecting pedestrians under adverse illumination
conditions. Our approach relies on a novel cross-modality learning framework and it is …
conditions. Our approach relies on a novel cross-modality learning framework and it is …
Exploring representation learning with cnns for frame-to-frame ego-motion estimation
Visual ego-motion estimation, or briefly visual odometry (VO), is one of the key building
blocks of modern SLAM systems. In the last decade, impressive results have been …
blocks of modern SLAM systems. In the last decade, impressive results have been …