6 papers
Dont Even Look Once: Synthesizing Features for Zero-Shot Detection
Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama
Zero-shot detection, namely, localizing both seen and unseen objects, increasingly gains importance for large-scale applications, with large number of object classes, since, collec…
Learning Classifiers for Domain Adaptation, Zero and Few-Shot Recognition Based on Learning Latent Semantic Parts
Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama
In computer vision applications, such as domain adaptation (DA), few shot learning (FSL) and zero-shot learning (ZSL), we encounter new objects and environments, for which insuffic…
Generalized Zero-Shot Recognition based on Visually Semantic Embedding
Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama
We propose a novel Generalized Zero-Shot learning (GZSL) method that is agnostic to both unseen images and unseen semantic vectors during training. Prior works in this context prop…
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations
Hanxiao Wang, Venkatesh Saligrama, Stan Sclaroff +1
We consider the problem of fine-grained classification on an edge camera device that has limited power. The edge device must sparingly interact with the cloud to minimize communica…
Person Re-Identification in Identity Regression Space
Hanxiao Wang, Xiatian Zhu, Shaogang Gong +1
Most existing person re-identification (re-id) methods are unsuitable for real-world deployment due to two reasons: Unscalability to large population size, and Inadaptability over…
Zero-Shot Detection
Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama
As we move towards large-scale object detection, it is unrealistic to expect annotated training data, in the form of bounding box annotations around objects, for all object classes…