344 citations · 1.3k across the 70 of their papers we have counts for
76 papers
LiFi: LiDAR Generation from Multi-View Images via Geometric and Semantic Collaborative Guidance
Sizhuo Zhou, Xiaosong Jia, Fanrui Zhang +10
Generating LiDAR point clouds from multi-view camera images is a valuable task with applications in controllable data synthesis, cross-modal simulation and various perception tasks…
CrossPortrait: Cross-Species Portrait Animation via Adversarial Motion Alignment
Gezhong Pan, Zhe Li, Yunfan Tao +7
Cross-species portrait animation, which aims to animate a source portrait of species A using a driving video of species B, is particularly challenging due to substantial anatomical…
Federated 3D Gaussian Splatting for Large-Scale Scene Reconstruction at Wireless Edge
Guanlin Wu, Chao Hu, Pu Chen +4
Three-dimensional (3D) Gaussian splatting (3D-GS) has emerged as a promising technique for large-scale scene reconstruction due to its high rendering efficiency and fidelity. Howev…
High-Fidelity 4D Hand-Object Capture via Multi-View Spatiotemporal Tracking and Physics-Aware Gaussians
Bo Peng, Xu Chen, Yi Gu +6
The growing demand for high-fidelity 4D hand-object interaction (HOI) data in embodied AI and spatial computing is currently bottlenecked by the reliance on pre-scanned object temp…
LaGen: Towards Autoregressive LiDAR Scene Generation
Sizhuo Zhou, Xiaosong Jia, Fanrui Zhang +7
Generative world models for autonomous driving (AD) are of great value in applications such as data augmentation, closed-loop simulation, and safety-critical scenario evaluation. U…
DualReg: Dual-Space Filtering and Reinforcement for Rigid Registration
Jiayi Li, Yuxin Yao, Qiuhang Lu +1
Noisy, partially overlapping data and the need for real-time processing pose major challenges for rigid registration. Considering that feature-based matching can handle large trans…
SparseLGS: Sparse View Language Embedded Gaussian Splatting
Jun Hu, Zhang Chen, Zhong Li +2
Recently, several studies have combined Gaussian Splatting to obtain scene representations with language embeddings for open-vocabulary 3D scene understanding. While these methods…
End-to-end Surface Optimization for Light Control
Yuou Sun, Bailin Deng, Juyong Zhang
Designing a freeform surface to reflect or refract light to achieve a target distribution is a challenging inverse problem. In this paper, we propose an end-to-end optimization str…
Semantic Communications for 3D Human Face Transmission with Neural Radiance Fields
Guanlin Wu, Zhonghao Lyu, Juyong Zhang +1
This paper investigates the transmission of three-dimensional (3D) human face content for immersive communication over a rate-constrained transmitter-receiver link. We propose a ne…
PICA: Physics-Integrated Clothed Avatar
Bo Peng, Yunfan Tao, Haoyu Zhan +2
We introduce PICA, a novel representation for high-fidelity animatable clothed human avatars with physics-accurate dynamics, even for loose clothing. Previous neural rendering-base…
Embracing Radiance Field Rendering in 6G: Over-the-Air Training and Inference with 3D Contents
Guanlin Wu, Zhonghao Lyu, Juyong Zhang +1
The efficient representation, transmission, and reconstruction of three-dimensional (3D) contents are becoming increasingly important for sixth-generation (6G) networks that aim to…
SPARE: Symmetrized Point-to-Plane Distance for Robust Non-Rigid 3D Registration
Yuxin Yao, Bailin Deng, Junhui Hou +1
Existing optimization-based methods for non-rigid registration typically minimize an alignment error metric based on the point-to-point or point-to-plane distance between correspon…
Oblique-MERF: Revisiting and Improving MERF for Oblique Photography
Xiaoyi Zeng, Kaiwen Song, Leyuan Yang +2
Neural implicit fields have established a new paradigm for scene representation, with subsequent work achieving high-quality real-time rendering. However, reconstructing 3D scenes…
Neural-ABC: Neural Parametric Models for Articulated Body with Clothes
Honghu Chen, Yuxin Yao, Juyong Zhang
In this paper, we introduce Neural-ABC, a novel parametric model based on neural implicit functions that can represent clothed human bodies with disentangled latent spaces for iden…
DynoSurf: Neural Deformation-based Temporally Consistent Dynamic Surface Reconstruction
Yuxin Yao, Siyu Ren, Junhui Hou +3
This paper explores the problem of reconstructing temporally consistent surfaces from a 3D point cloud sequence without correspondence. To address this challenging task, we propose…
Hybrid Explicit Representation for Ultra-Realistic Head Avatars
Hongrui Cai, Yuting Xiao, Xuan Wang +5
We introduce a novel approach to creating ultra-realistic head avatars and rendering them in real-time (>30fps at resolution). First, we propose a hybrid explici…
HeadRecon: High-Fidelity 3D Head Reconstruction from Monocular Video
Xueying Wang, Juyong Zhang
Recently, the reconstruction of high-fidelity 3D head models from static portrait image has made great progress. However, most methods require multi-view or multi-illumination info…
City-on-Web: Real-time Neural Rendering of Large-scale Scenes on the Web
Kaiwen Song, Xiaoyi Zeng, Chenqu Ren +1
Existing neural radiance field-based methods can achieve real-time rendering of small scenes on the web platform. However, extending these methods to large-scale scenes still poses…
FlashAvatar: High-fidelity Head Avatar with Efficient Gaussian Embedding
Jun Xiang, Xuan Gao, Yudong Guo +1
We propose FlashAvatar, a novel and lightweight 3D animatable avatar representation that could reconstruct a digital avatar from a short monocular video sequence in minutes and ren…
CosAvatar: Consistent and Animatable Portrait Video Tuning with Text Prompt
Haiyao Xiao, Chenglai Zhong, Xuan Gao +2
Recently, text-guided digital portrait editing has attracted more and more attentions. However, existing methods still struggle to maintain consistency across time, expression, and…
-Sampler: An Model Guided Volume Sampling for NeRF
Liangchen Li, Juyong Zhang
Since being proposed, Neural Radiance Fields (NeRF) have achieved great success in related tasks, mainly adopting the hierarchical volume sampling (HVS) strategy for volume renderi…
MetaHead: An Engine to Create Realistic Digital Head
Dingyun Zhang, Chenglai Zhong, Yudong Guo +2
Collecting and labeling training data is one important step for learning-based methods because the process is time-consuming and biased. For face analysis tasks, although some gene…
IntrinsicNGP: Intrinsic Coordinate based Hash Encoding for Human NeRF
Bo Peng, Jun Hu, Jingtao Zhou +2
Recently, many works have been proposed to utilize the neural radiance field for novel view synthesis of human performers. However, most of these methods require hours of training,…
Flattening-Net: Deep Regular 2D Representation for 3D Point Cloud Analysis
Qijian Zhang, Junhui Hou, Yue Qian +3
Point clouds are characterized by irregularity and unstructuredness, which pose challenges in efficient data exploitation and discriminative feature extraction. In this paper, we p…