Search Results for author: Lan Xu

Found 33 papers, 10 papers with code

RobustFusion: Human Volumetric Capture with Data-driven Visual Cues using a RGBD Camera

no code implementations ECCV 2020 Zhuo Su, Lan Xu, Zerong Zheng, Tao Yu, Yebin Liu, Lu Fang

To enable robust tracking, we embrace both the initial model and the various visual cues into a novel performance capture scheme with hybrid motion optimization and semantic volumetric fusion, which can successfully capture challenging human motions under the monocular setting without pre-scanned detailed template and owns the reinitialization ability to recover from tracking failures and the disappear-reoccur scenarios.

STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes

1 code implementation3 Apr 2022 Peishan Cong, Xinge Zhu, Feng Qiao, Yiming Ren, Xidong Peng, Yuenan Hou, Lan Xu, Ruigang Yang, Dinesh Manocha, Yuexin Ma

In addition, considering the property of sparse global distribution and density-varying local distribution of pedestrians, we further propose a novel method, Density-aware Hierarchical heatmap Aggregation (DHA), to enhance pedestrian perception in crowded scenes.

Frame Pedestrian Detection

LiDARCap: Long-range Marker-less 3D Human Motion Capture with LiDAR Point Clouds

no code implementations28 Mar 2022 Jialian Li, Jingyi Zhang, Zhiyong Wang, Siqi Shen, Chenglu Wen, Yuexin Ma, Lan Xu, Jingyi Yu, Cheng Wang

Quantitative and qualitative experiments show that our method outperforms the techniques based only on RGB images.

HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR

1 code implementation17 Mar 2022 Yudi Dai, Yitai Lin, Chenglu Wen, Siqi Shen, Lan Xu, Jingyi Yu, Yuexin Ma, Cheng Wang

We propose Human-centered 4D Scene Capture (HSC4D) to accurately and efficiently create a dynamic digital world, containing large-scale indoor-outdoor scenes, diverse human motions, and rich interactions between humans and environments.

3D Human Pose Estimation Autonomous Driving

NeReF: Neural Refractive Field for Fluid Surface Reconstruction and Implicit Representation

no code implementations8 Mar 2022 Ziyu Wang, Wei Yang, Junming Cao, Lan Xu, Junqing Yu, Jingyi Yu

We present a novel neural refractive field(NeReF) to recover wavefront of transparent fluids by simultaneously estimating the surface position and normal of the fluid front.

Surface Reconstruction

NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactions

no code implementations25 Feb 2022 Yuheng Jiang, Suyi Jiang, Guoxing Sun, Zhuo Su, Kaiwen Guo, Minye Wu, Jingyi Yu, Lan Xu

In this paper, we propose NeuralHOFusion, a neural approach for volumetric human-object capture and rendering using sparse consumer RGBD sensors.

Human-Object Interaction Detection Multi-Task Learning +1

Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time

no code implementations17 Feb 2022 Liao Wang, Jiakai Zhang, Xinhang Liu, Fuqiang Zhao, Yanshun Zhang, Yingliang Zhang, Minye Wu, Lan Xu, Jingyi Yu

In this paper, we present a novel Fourier PlenOctree (FPO) technique to tackle efficient neural modeling and real-time rendering of dynamic scenes captured under the free-view video (FVV) setting.

NeuVV: Neural Volumetric Videos with Immersive Rendering and Editing

no code implementations12 Feb 2022 Jiakai Zhang, Liao Wang, Xinhang Liu, Fuqiang Zhao, Minzhang Li, Haizhao Dai, Boyuan Zhang, Wei Yang, Lan Xu, Jingyi Yu

We further develop a hybrid neural-rasterization rendering framework to support consumer-level VR headsets so that the aforementioned volumetric video viewing and editing, for the first time, can be conducted immersively in virtual 3D space.

3D Reconstruction

Artemis: Articulated Neural Pets with Appearance and Motion synthesis

1 code implementation11 Feb 2022 Haimin Luo, Teng Xu, Yuheng Jiang, Chenglin Zhou, QIwei Qiu, Yingliang Zhang, Wei Yang, Lan Xu, Jingyi Yu

Our ARTEMIS enables interactive motion control, real-time animation, and photo-realistic rendering of furry animals.

motion synthesis

Video-driven Neural Physically-based Facial Asset for Production

no code implementations11 Feb 2022 Longwen Zhang, Chuxiao Zeng, Qixuan Zhang, Hongyang Lin, Ruixiang Cao, Wei Yang, Lan Xu, Jingyi Yu

We then model the facial expression, geometry and physically-based textures using separate VAEs with a global MLP-based expression mapping across the latent spaces, to preserve characteristics across respective attributes while maintaining explicit controls over geometry and texture.

motion retargeting Texture Synthesis

NIMBLE: A Non-rigid Hand Model with Bones and Muscles

no code implementations9 Feb 2022 Yuwei Li, Longwen Zhang, Zesong Qiu, Yingwenqi Jiang, Nianyi Li, Yuexin Ma, Yuyao Zhang, Lan Xu, Jingyi Yu

Emerging Metaverse applications demand reliable, accurate, and photorealistic reproductions of human hands to perform sophisticated operations as if in the physical world.

HumanNeRF: Efficiently Generated Human Radiance Field from Sparse Inputs

no code implementations6 Dec 2021 Fuqiang Zhao, Wei Yang, Jiakai Zhang, Pei Lin, Yingliang Zhang, Jingyi Yu, Lan Xu

The raw HumanNeRF can already produce reasonable rendering on sparse video inputs of unseen subjects and camera settings.

Frame

iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Rendering

no code implementations12 Aug 2021 Liao Wang, Ziyu Wang, Pei Lin, Yuheng Jiang, Xin Suo, Minye Wu, Lan Xu, Jingyi Yu

To fill this gap, in this paper we propose a neural interactive bullet-time generator (iButter) for photo-realistic human free-viewpoint rendering from dense RGB streams, which enables flexible and interactive design for human bullet-time visual effects.

Video Generation

Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions

no code implementations1 Aug 2021 Guoxing Sun, Xin Chen, Yizhang Chen, Anqi Pang, Pei Lin, Yuheng Jiang, Lan Xu, Jingya Wang, Jingyi Yu

In this paper, we propose a neural human performance capture and rendering system to generate both high-quality geometry and photo-realistic texture of both human and objects under challenging interaction scenarios in arbitrary novel views, from only sparse RGB streams.

Human-Object Interaction Detection Neural Rendering +2

Neural Relighting and Expression Transfer On Video Portraits

no code implementations30 Jul 2021 Youjia Wang, Taotao Zhou, Minzhang Li, Teng Xu, Minye Wu, Lan Xu, Jingyi Yu

We present a neural relighting and expression transfer technique to transfer the facial expressions from a source performer to a portrait video of a target performer while enabling dynamic relighting.

Frame Multi-Task Learning +1

Few-shot Neural Human Performance Rendering from Sparse RGBD Videos

no code implementations14 Jul 2021 Anqi Pang, Xin Chen, Haimin Luo, Minye Wu, Jingyi Yu, Lan Xu

To fill this gap, in this paper we propose a few-shot neural human rendering approach (FNHR) from only sparse RGBD inputs, which exploits the temporal and spatial redundancy to generate photo-realistic free-view output of human activities.

Neural Rendering

IREM: High-Resolution Magnetic Resonance (MR) Image Reconstruction via Implicit Neural Representation

no code implementations29 Jun 2021 Qing Wu, Yuwei Li, Lan Xu, Ruiming Feng, Hongjiang Wei, Qing Yang, Boliang Yu, Xiaozhao Liu, Jingyi Yu, Yuyao Zhang

For collecting high-quality high-resolution (HR) MR image, we propose a novel image reconstruction network named IREM, which is trained on multiple low-resolution (LR) MR images and achieve an arbitrary up-sampling rate for HR image reconstruction.

Image Reconstruction Super-Resolution

PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging

1 code implementation21 Jun 2021 Yuwei Li, Minye Wu, Yuyao Zhang, Lan Xu, Jingyi Yu

Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare.

Action Understanding

RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions from Monocular RGBD Stream

no code implementations30 Apr 2021 Zhuo Su, Lan Xu, Dawei Zhong, Zhong Li, Fan Deng, Shuxue Quan, Lu Fang

To fill this gap, in this paper, we propose RobustFusion, a robust volumetric performance reconstruction system for human-object interaction scenarios using only a single RGBD sensor, which combines various data-driven visual and interaction cues to handle the complex interaction patterns and severe occlusions.

Disentanglement Human-Object Interaction Detection +3

Editable Free-viewpoint Video Using a Layered Neural Representation

1 code implementation30 Apr 2021 Jiakai Zhang, Xinhang Liu, Xinyi Ye, Fuqiang Zhao, Yanshun Zhang, Minye Wu, Yingliang Zhang, Lan Xu, Jingyi Yu

Such layered representation supports fully perception and realistic manipulation of the dynamic scene whilst still supporting a free viewing experience in a wide range.

Disentanglement Scene Parsing +1

SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos

1 code implementation23 Apr 2021 Xin Chen, Anqi Pang, Wei Yang, Yuexin Ma, Lan Xu, Jingyi Yu

In this paper, we propose SportsCap -- the first approach for simultaneously capturing 3D human motions and understanding fine-grained actions from monocular challenging sports video input.

Action Assessment Markerless Motion Capture

MirrorNeRF: One-shot Neural Portrait Radiance Field from Multi-mirror Catadioptric Imaging

no code implementations6 Apr 2021 Ziyu Wang, Liao Wang, Fuqiang Zhao, Minye Wu, Lan Xu, Jingyi Yu

In this paper, we propose MirrorNeRF - a one-shot neural portrait free-viewpoint rendering approach using a catadioptric imaging system with multiple sphere mirrors and a single high-resolution digital camera, which is the first to combine neural radiance field with catadioptric imaging so as to enable one-shot photo-realistic human portrait reconstruction and rendering, in a low-cost and casual capture setting.

Convolutional Neural Opacity Radiance Fields

1 code implementation5 Apr 2021 Haimin Luo, Anpei Chen, Qixuan Zhang, Bai Pang, Minye Wu, Lan Xu, Jingyi Yu

In this paper, we propose a novel scheme to generate opacity radiance fields with a convolutional neural renderer for fuzzy objects, which is the first to combine both explicit opacity supervision and convolutional mechanism into the neural radiance field framework so as to enable high-quality appearance and global consistent alpha mattes generation in arbitrary novel views.

Neural Video Portrait Relighting in Real-time via Consistency Modeling

1 code implementation ICCV 2021 Longwen Zhang, Qixuan Zhang, Minye Wu, Jingyi Yu, Lan Xu

In this paper, we propose a neural approach for real-time, high-quality and coherent video portrait relighting, which jointly models the semantic, temporal and lighting consistency using a new dynamic OLAT dataset.

Disentanglement Single-Image Portrait Relighting

GNeRF: GAN-based Neural Radiance Field without Posed Camera

1 code implementation ICCV 2021 Quan Meng, Anpei Chen, Haimin Luo, Minye Wu, Hao Su, Lan Xu, Xuming He, Jingyi Yu

We introduce GNeRF, a framework to marry Generative Adversarial Networks (GAN) with Neural Radiance Field (NeRF) reconstruction for the complex scenarios with unknown and even randomly initialized camera poses.

Novel View Synthesis

NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering using RGB Cameras

no code implementations CVPR 2021 Xin Suo, Yuheng Jiang, Pei Lin, Yingliang Zhang, Kaiwen Guo, Minye Wu, Lan Xu

4D reconstruction and rendering of human activities is critical for immersive VR/AR experience. Recent advances still fail to recover fine geometry and texture results with the level of detail present in the input images from sparse multi-view RGB cameras.

Multi-Task Learning

ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal References

1 code implementation CVPR 2021 Yannan He, Anqi Pang, Xin Chen, Han Liang, Minye Wu, Yuexin Ma, Lan Xu

We propose a hybrid motion inference stage with a generation network, which utilizes a temporal encoder-decoder to extract the motion details from the pair-wise sparse-view reference, as well as a motion discriminator to utilize the unpaired marker-based references to extract specific challenging motion characteristics in a data-driven manner.

OccuSeg: Occupancy-aware 3D Instance Segmentation

no code implementations CVPR 2020 Lei Han, Tian Zheng, Lan Xu, Lu Fang

3D instance segmentation, with a variety of applications in robotics and augmented reality, is in large demands these days.

3D Instance Segmentation Multi-Task Learning +1

Beyond SIFT using Binary features for Loop Closure Detection

no code implementations18 Sep 2017 Lei Han, Guyue Zhou, Lan Xu, Lu Fang

The proposed system originates from our previous work Multi-Index hashing for Loop closure Detection (MILD), which employs Multi-Index Hashing (MIH)~\cite{greene1994multi} for Approximate Nearest Neighbor (ANN) search of binary features.

Loop Closure Detection

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras

no code implementations29 Oct 2016 Lan Xu, Lu Fang, Wei Cheng, Kaiwen Guo, Guyue Zhou, Qionghai Dai, Yebin Liu

We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera.

Markerless Motion Capture Visual Odometry

Cannot find the paper you are looking for? You can Submit a new open access paper.