activity
20192022
most citedMultiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction

76 citations · 156 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20226 cited

HyperDet3D: Learning a Scene-conditioned 3D Object Detector

Yu Zheng, Yueqi Duan, Jiwen Lu +2

A bathtub in a library, a sink in an office, a bed in a laundry room -- the counter-intuition suggests that scene provides important prior knowledge for 3D object detection, which…

cs.CV202174 cited

CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis

Peng Zhou, Lingxi Xie, Bingbing Ni +1

The style-based GAN (StyleGAN) architecture achieved state-of-the-art results for generating high-quality images, but it lacks explicit and precise control over camera poses. The r…

cs.CV202176 cited

Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction

Maosen Li, Siheng Chen, Yangheng Zhao +3

We propose a multiscale spatio-temporal graph neural network (MST-GNN) to predict the future 3D skeleton-based human poses in an action-category-agnostic manner. The core of MST-GN…

cs.CV2020

CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing

Xuanhong Chen, Bingbing Ni, Naiyuan Liu +4

In contrast to great success of memory-consuming face editing methods at a low resolution, to manipulate high-resolution (HR) facial images, i.e., typically larger than 7682 pixels…

cs.CV2019

Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling

Jiancheng Yang, Qiang Zhang, Bingbing Ni +4

Geometric deep learning is increasingly important thanks to the popularity of 3D sensors. Inspired by the recent advances in NLP domain, the self-attention transformer is introduce…