activity
20182021
most citedExposing Deep-faked Videos by Anomalous Co-motion Pattern Detection

19 citations · 38 across the 8 of their papers we have counts for

collaborators

14 papers

cs.CV2021

Morphable Detector for Object Detection on Demand

Xiangyun Zhao, Xu Zou, Ying Wu

Many emerging applications of intelligent robots need to explore and understand new environments, where it is desirable to detect objects of novel classes on the fly with minimum o…

cs.CV20211 cited

Unsupervised Embedding Learning from Uncertainty Momentum Modeling

Jiahuan Zhou, Yansong Tang, Bing Su +1

Existing popular unsupervised embedding learning methods focus on enhancing the instance-level local discrimination of the given unlabeled images by exploring various negative data…

cs.CV20211 cited

Beyond Visual Attractiveness: Physically Plausible Single Image HDR Reconstruction for Spherical Panoramas

Wei Wei, Li Guan, Yue Liu +4

HDR reconstruction is an important task in computer vision with many industrial needs. The traditional approaches merge multiple exposure shots to generate HDRs that correspond to…

cs.RO20212 cited

MetaView: Few-shot Active Object Recognition

Wei Wei, Haonan Yu, Haichao Zhang +2

In robot sensing scenarios, instead of passively utilizing human captured views, an agent should be able to actively choose informative viewpoints of a 3D object as discriminative…

cs.CV2020

Contrastive Learning for Label-Efficient Semantic Segmentation

Xiangyun Zhao, Raviteja Vemulapalli, Philip Mansfield +4

Collecting labeled data for the task of semantic segmentation is expensive and time-consuming, as it requires dense pixel-level annotations. While recent Convolutional Neural Netwo…

cs.CV20203 cited

Object Detection with a Unified Label Space from Multiple Datasets

Xiangyun Zhao, Samuel Schulter, Gaurav Sharma +3

Given multiple datasets with different label spaces, the goal of this work is to train a single object detector predicting over the union of all the label spaces. The practical ben…