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20212026
most citedMove As You Like: Image Animation in E-Commerce Scenario

6 citations · 13 across the 17 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.CV2022

Video Object of Interest Segmentation

Siyuan Zhou, Chunru Zhan, Biao Wang +3

In this work, we present a new computer vision task named video object of interest segmentation (VOIS). Given a video and a target image of interest, our objective is to simultaneo…

cs.CV2022★ 1 cited

Motion and Appearance Adaptation for Cross-Domain Motion Transfer

Borun Xu, Biao Wang, Jinhong Deng +5

Motion transfer aims to transfer the motion of a driving video to a source image. When there are considerable differences between object in the driving video and that in the source…

cs.CV2022

Motion Transformer for Unsupervised Image Animation

Jiale Tao, Biao Wang, Tiezheng Ge +3

Image animation aims to animate a source image by using motion learned from a driving video. Current state-of-the-art methods typically use convolutional neural networks (CNNs) to…

cs.CV2022★ 2 cited

Spatio-Temporal Relation Learning for Video Anomaly Detection

Hui Lv, Zhen Cui, Biao Wang +1

Anomaly identification is highly dependent on the relationship between the object and the scene, as different/same object actions in same/different scenes may lead to various degre…

cs.CV2022★ 1 cited

Structure-Aware Motion Transfer with Deformable Anchor Model

Jiale Tao, Biao Wang, Borun Xu +4

Given a source image and a driving video depicting the same object type, the motion transfer task aims to generate a video by learning the motion from the driving video while prese…

cs.CV2022★ 1 cited

Learning Pixel-Level Distinctions for Video Highlight Detection

Fanyue Wei, Biao Wang, Tiezheng Ge +3

The goal of video highlight detection is to select the most attractive segments from a long video to depict the most interesting parts of the video. Existing methods typically focu…

cs.CV2022

Estimation of Reliable Proposal Quality for Temporal Action Detection

Junshan Hu, Chaoxu guo, Liansheng Zhuang +4

Temporal action detection (TAD) aims to locate and recognize the actions in an untrimmed video. Anchor-free methods have made remarkable progress which mainly formulate TAD into tw…