activity
20142021
most citedCNN: Single-label to Multi-label

829 citations · 1.2k across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Image-to-Video Generation via 3D Facial Dynamics

Xiaoguang Tu, Yingtian Zou, Jian Zhao +8

We present a versatile model, FaceAnime, for various video generation tasks from still images. Video generation from a single face image is an interesting problem and usually tackl…

cs.CV2019★ 3 cited

Very Long Natural Scenery Image Prediction by Outpainting

Zongxin Yang, Jian Dong, Ping Liu +2

Comparing to image inpainting, image outpainting receives less attention due to two challenges in it. The first challenge is how to keep the spatial and content consistency between…

cs.CV2016★ 6 cited

Video Scene Parsing with Predictive Feature Learning

Xiaojie Jin, Xin Li, Huaxin Xiao +9

In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we co…

cs.CV2016★ 4 cited

Collaborative Layer-wise Discriminative Learning in Deep Neural Networks

Xiaojie Jin, Yunpeng Chen, Jian Dong +2

Intermediate features at different layers of a deep neural network are known to be discriminative for visual patterns of different complexities. However, most existing works ignore…

cs.CV2016★ 4 cited

Attentive Contexts for Object Detection

Jianan Li, Yunchao Wei, Xiaodan Liang +4

Modern deep neural network based object detection methods typically classify candidate proposals using their interior features. However, global and local surrounding contexts that…

cs.CV2015★ 326 cited

Deep Human Parsing with Active Template Regression

Xiaodan Liang, Si Liu, Xiaohui Shen +5

In this work, the human parsing task, namely decomposing a human image into semantic fashion/body regions, is formulated as an Active Template Regression (ATR) problem, where the n…

cs.CV2014★ 829 cited

CNN: Single-label to Multi-label

Yunchao Wei, Wei Xia, Junshi Huang +4

Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still rema…