Search Results for author: Liang Pan

Found 19 papers, 16 papers with code

AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

1 code implementation17 May 2022 Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai, Lei Yang, Ziwei Liu

Our key insight is to take advantage of the powerful vision-language model CLIP for supervising neural human generation, in terms of 3D geometry, texture and animation.

Language Modelling motion synthesis +1

Neural MoCon: Neural Motion Control for Physically Plausible Human Motion Capture

no code implementations26 Mar 2022 Buzhen Huang, Liang Pan, Yuan Yang, Jingyi Ju, Yangang Wang

Our key-idea is to use real physical supervisions to train a target pose distribution prior for sampling-based motion control to capture physically plausible human motion.

Versatile Multi-Modal Pre-Training for Human-Centric Perception

1 code implementation25 Mar 2022 Fangzhou Hong, Liang Pan, Zhongang Cai, Ziwei Liu

To tackle the challenges, we design the novel Dense Intra-sample Contrastive Learning and Sparse Structure-aware Contrastive Learning targets by hierarchically learning a modal-invariant latent space featured with continuous and ordinal feature distribution and structure-aware semantic consistency.

Contrastive Learning Human Parsing +1

TCTrack: Temporal Contexts for Aerial Tracking

1 code implementation3 Mar 2022 Ziang Cao, Ziyuan Huang, Liang Pan, Shiwei Zhang, Ziwei Liu, Changhong Fu

Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers.

Garment4D: Garment Reconstruction from Point Cloud Sequences

1 code implementation NeurIPS 2021 Fangzhou Hong, Liang Pan, Zhongang Cai, Ziwei Liu

The main challenges are two-fold: 1) effective 3D feature learning for fine details, and 2) capture of garment dynamics caused by the interaction between garments and the human body, especially for loose garments like skirts.

PTTR: Relational 3D Point Cloud Object Tracking with Transformer

1 code implementation6 Dec 2021 Changqing Zhou, Zhipeng Luo, Yueru Luo, Tianrui Liu, Liang Pan, Zhongang Cai, Haiyu Zhao, Shijian Lu

In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in the current search point cloud given a template point cloud.

3D Object Tracking Object Tracking

Balanced Chamfer Distance as a Comprehensive Metric for Point Cloud Completion

1 code implementation NeurIPS 2021 Tong Wu, Liang Pan, Junzhe Zhang, Tai Wang, Ziwei Liu, Dahua Lin

We adopt DCD to evaluate the point cloud completion task, where experimental results show that DCD pays attention to both the overall structure and local geometric details and provides a more reliable evaluation even when CD and EMD contradict each other.

Point Cloud Completion

Robust Partial-to-Partial Point Cloud Registration in a Full Range

1 code implementation30 Nov 2021 Liang Pan, Zhongang Cai, Ziwei Liu

\textbf{3)} Based on a synergy of hierarchical graph networks and graphical modeling, we propose the {H}ierarchical {G}raphical {M}odeling (\textbf{HGM}) architecture to encode robust descriptors consisting of i) a unary term learned from {\textit{RI}} features; and ii) multiple smoothness terms encoded from neighboring point relations at different scales through our TPT modules.

Graph Matching Point Cloud Registration

Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion

1 code implementation24 Nov 2021 Tong Wu, Liang Pan, Junzhe Zhang, Tai Wang, Ziwei Liu, Dahua Lin

We adopt DCD to evaluate the point cloud completion task, where experimental results show that DCD pays attention to both the overall structure and local geometric details and provides a more reliable evaluation even when CD and EMD contradict each other.

Point Cloud Completion

TAda! Temporally-Adaptive Convolutions for Video Understanding

2 code implementations ICLR 2022 Ziyuan Huang, Shiwei Zhang, Liang Pan, Zhiwu Qing, Mingqian Tang, Ziwei Liu, Marcelo H. Ang Jr

This work presents Temporally-Adaptive Convolutions (TAdaConv) for video understanding, which shows that adaptive weight calibration along the temporal dimension is an efficient way to facilitate modelling complex temporal dynamics in videos.

Ranked #31 on Action Recognition on Something-Something V2 (using extra training data)

Action Classification Action Recognition +2

Unsupervised 3D Shape Completion through GAN Inversion

no code implementations CVPR 2021 Junzhe Zhang, Xinyi Chen, Zhongang Cai, Liang Pan, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Bo Dai, Chen Change Loy

In contrast to previous fully supervised approaches, in this paper we present ShapeInversion, which introduces Generative Adversarial Network (GAN) inversion to shape completion for the first time.

Variational Relational Point Completion Network

1 code implementation CVPR 2021 Liang Pan, Xinyi Chen, Zhongang Cai, Junzhe Zhang, Haiyu Zhao, Shuai Yi, Ziwei Liu

In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds.

Point Cloud Completion

Robust 6D Object Pose Estimation by Learning RGB-D Features

1 code implementation29 Feb 2020 Meng Tian, Liang Pan, Marcelo H. Ang Jr, Gim Hee Lee

Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping.

6D Pose Estimation using RGB

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points

1 code implementation23 Jul 2019 Liang Pan, Chee-Meng Chew, Gim Hee Lee

Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge features in point clouds.

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