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20162019
most citedZero-Shot Detection

105 citations · 133 across the 9 of their papers we have counts for

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9 papers · 1 filter

cs.CV2019★ 5 cited

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…

cs.CV2019★ 1 cited

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…

cs.CV2018★ 9 cited

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…

cs.CV2018

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…

cs.CV2018

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…

cs.CV2018★ 105 cited

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…

cs.CV2017★ 10 cited

Deep Reinforcement Learning Attention Selection for Person Re-Identification

Xu Lan, Hanxiao Wang, Shaogang Gong +1

Existing person re-identification (re-id) methods assume the provision of accurately cropped person bounding boxes with minimum background noise, mostly by manually cropping. This…

cs.CV2016★ 3 cited

Highly Efficient Regression for Scalable Person Re-Identification

Hanxiao Wang, Shaogang Gong, Tao Xiang

Existing person re-identification models are poor for scaling up to large data required in real-world applications due to: (1) Complexity: They employ complex models for optimal pe…

cs.CV2016

Human-In-The-Loop Person Re-Identification

Hanxiao Wang, Shaogang Gong, Xiatian Zhu +1

Current person re-identification (re-id) methods assume that (1) pre-labelled training data are available for every camera pair, (2) the gallery size for re-identification is moder…