activity
20182021
most citedImproving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems

16 citations · 52 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CV2021

Detailed Avatar Recovery from Single Image

Hao Zhu, Xinxin Zuo, Haotian Yang +3

This paper presents a novel framework to recover \emph{detailed} avatar from a single image. It is a challenging task due to factors such as variations in human shapes, body poses,…

eess.IV20211 cited

End-to-end Neural Video Coding Using a Compound Spatiotemporal Representation

Haojie Liu, Ming Lu, Zhiqi Chen +3

Recent years have witnessed rapid advances in learnt video coding. Most algorithms have solely relied on the vector-based motion representation and resampling (e.g., optical flow b…

cs.CV20219 cited

Audio-Driven Emotional Video Portraits

Xinya Ji, Hang Zhou, Kaisiyuan Wang +4

Despite previous success in generating audio-driven talking heads, most of the previous studies focus on the correlation between speech content and the mouth shape. Facial emotion,…

cs.CV202016 cited

Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems

Kailai Zhou, Linsen Chen, Xun Cao

Multispectral pedestrian detection is capable of adapting to insufficient illumination conditions by leveraging color-thermal modalities. On the other hand, it is still lacking of…

eess.IV20204 cited

Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model

Haojie Liu, Ming Lu, Zhan Ma +4

Over the past two decades, traditional block-based video coding has made remarkable progress and spawned a series of well-known standards such as MPEG-4, H.264/AVC and H.265/HEVC.…

cs.CV202012 cited

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction

Haotian Yang, Hao Zhu, Yanru Wang +4

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single i…