Search Results for author: Liang Pan

Found 43 papers, 32 papers with code

Exploiting Hierarchical Interactions for Protein Surface Learning

1 code implementation17 Jan 2024 Yiqun Lin, Liang Pan, Yi Li, Ziwei Liu, Xiaomeng Li

In this paper, we present a principled framework based on deep learning techniques, namely Hierarchical Chemical and Geometric Feature Interaction Network (HCGNet), for protein surface analysis by bridging chemical and geometric features with hierarchical interactions.

InsActor: Instruction-driven Physics-based Characters

no code implementations NeurIPS 2023 Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Xiao Ma, Liang Pan, Ziwei Liu

Generating animation of physics-based characters with intuitive control has long been a desirable task with numerous applications.

Motion Planning

DreamGaussian4D: Generative 4D Gaussian Splatting

1 code implementation28 Dec 2023 Jiawei Ren, Liang Pan, Jiaxiang Tang, Chi Zhang, Ang Cao, Gang Zeng, Ziwei Liu

Remarkable progress has been made in 4D content generation recently.

Digital Life Project: Autonomous 3D Characters with Social Intelligence

no code implementations7 Dec 2023 Zhongang Cai, Jianping Jiang, Zhongfei Qing, Xinying Guo, Mingyuan Zhang, Zhengyu Lin, Haiyi Mei, Chen Wei, Ruisi Wang, Wanqi Yin, Xiangyu Fan, Han Du, Liang Pan, Peng Gao, Zhitao Yang, Yang Gao, Jiaqi Li, Tianxiang Ren, Yukun Wei, Xiaogang Wang, Chen Change Loy, Lei Yang, Ziwei Liu

In this work, we present Digital Life Project, a framework utilizing language as the universal medium to build autonomous 3D characters, who are capable of engaging in social interactions and expressing with articulated body motions, thereby simulating life in a digital environment.

Motion Captioning Motion Synthesis

Large-Vocabulary 3D Diffusion Model with Transformer

no code implementations14 Sep 2023 Ziang Cao, Fangzhou Hong, Tong Wu, Liang Pan, Ziwei Liu

To this end, we propose a novel triplane-based 3D-aware Diffusion model with TransFormer, DiffTF, for handling challenges via three aspects.

PointHPS: Cascaded 3D Human Pose and Shape Estimation from Point Clouds

no code implementations28 Aug 2023 Zhongang Cai, Liang Pan, Chen Wei, Wanqi Yin, Fangzhou Hong, Mingyuan Zhang, Chen Change Loy, Lei Yang, Ziwei Liu

To tackle these challenges, we propose a principled framework, PointHPS, for accurate 3D HPS from point clouds captured in real-world settings, which iteratively refines point features through a cascaded architecture.

3D human pose and shape estimation

Towards Real-World Visual Tracking with Temporal Contexts

1 code implementation20 Aug 2023 Ziang Cao, Ziyuan Huang, Liang Pan, Shiwei Zhang, Ziwei Liu, Changhong Fu

To handle those problems, we propose a two-level framework (TCTrack) that can exploit temporal contexts efficiently.

Visual Tracking

HumanLiff: Layer-wise 3D Human Generation with Diffusion Model

no code implementations18 Aug 2023 Shoukang Hu, Fangzhou Hong, Tao Hu, Liang Pan, Haiyi Mei, Weiye Xiao, Lei Yang, Ziwei Liu

In this work, we propose HumanLiff, the first layer-wise 3D human generative model with a unified diffusion process.

Neural Rendering

Synthesizing Physically Plausible Human Motions in 3D Scenes

1 code implementation17 Aug 2023 Liang Pan, Jingbo Wang, Buzhen Huang, Junyu Zhang, Haofan Wang, Xu Tang, Yangang Wang

Experimental results demonstrate that our framework can synthesize physically plausible long-term human motions in complex 3D scenes.

RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions

1 code implementation13 Apr 2023 Shaoyuan Xie, Lingdong Kong, Wenwei Zhang, Jiawei Ren, Liang Pan, Kai Chen, Ziwei Liu

Our experiments further demonstrate that pre-training and depth-free BEV transformation has the potential to enhance out-of-distribution robustness.

Robust Camera Only 3D Object Detection

SHERF: Generalizable Human NeRF from a Single Image

1 code implementation ICCV 2023 Shoukang Hu, Fangzhou Hong, Liang Pan, Haiyi Mei, Lei Yang, Ziwei Liu

To this end, we propose a bank of 3D-aware hierarchical features, including global, point-level, and pixel-aligned features, to facilitate informative encoding.

3D Human Reconstruction

EVA3D: Compositional 3D Human Generation from 2D Image Collections

1 code implementation10 Oct 2022 Fangzhou Hong, Zhaoxi Chen, Yushi Lan, Liang Pan, Ziwei Liu

At the core of EVA3D is a compositional human NeRF representation, which divides the human body into local parts.

MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

2 code implementations31 Aug 2022 Mingyuan Zhang, Zhongang Cai, Liang Pan, Fangzhou Hong, Xinying Guo, Lei Yang, Ziwei Liu

Instead of a deterministic language-motion mapping, MotionDiffuse generates motions through a series of denoising steps in which variations are injected.

Denoising Motion Synthesis

Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer

1 code implementation10 Aug 2022 Zhipeng Luo, Changqing Zhou, Liang Pan, Gongjie Zhang, Tianrui Liu, Yueru Luo, Haiyu Zhao, Ziwei Liu, Shijian Lu

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

3D Object Tracking Autonomous Driving +3

TransPillars: Coarse-to-Fine Aggregation for Multi-Frame 3D Object Detection

no code implementations4 Aug 2022 Zhipeng Luo, Gongjie Zhang, Changqing Zhou, Tianrui Liu, Shijian Lu, Liang Pan

3D object detection using point clouds has attracted increasing attention due to its wide applications in autonomous driving and robotics.

3D Object Detection Autonomous Driving +3

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 implementations CVPR 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 implementation CVPR 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 implementation CVPR 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.

Garment Reconstruction

PTTR: Relational 3D Point Cloud Object Tracking with Transformer

1 code implementation CVPR 2022 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 +3

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 #62 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.

Generative Adversarial Network valid

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

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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