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20102022
most citedRecent Advances in Convolutional Neural Networks

325 citations · 2k across the 89 of their papers we have counts for

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Showing 2019Show all

17 papers · 1 filter

cs.CV2019★ 1 cited

Recovering Facial Reflectance and Geometry from Multi-view Images

Guoxian Song, Jianmin Zheng, Jianfei Cai +1

While the problem of estimating shapes and diffuse reflectances of human faces from images has been extensively studied, there is relatively less work done on recovering the specul…

stat.ML2019★ 2 cited

Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods

Haitao Liu, Yew-Soon Ong, Ziwei Yu +2

Gaussian process classification (GPC) provides a flexible and powerful statistical framework describing joint distributions over function space. Conventional GPCs however suffer fr…

cs.CV2019★ 3 cited

Watch It Twice: Video Captioning with a Refocused Video Encoder

Xiangxi Shi, Jianfei Cai, Shafiq Joty +1

With the rapid growth of video data and the increasing demands of various applications such as intelligent video search and assistance toward visually-impaired people, video captio…

cs.CV2019★ 5 cited

Improving Deep Lesion Detection Using 3D Contextual and Spatial Attention

Qingyi Tao, Zongyuan Ge, Jianfei Cai +2

Lesion detection from computed tomography (CT) scans is challenging compared to natural object detection because of two major reasons: small lesion size and small inter-class varia…

cs.CV2019

Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

Lu Sheng, Jianfei Cai, Tat-Jen Cham +2

In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy oc…

cs.CV2019★ 44 cited

Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network

Boyi Jiang, Juyong Zhang, Jianfei Cai +1

Human bodies exhibit various shapes for different identities or poses, but the body shape has certain similarities in structure and thus can be embedded in a low-dimensional space.…