28 citations · 60 across the 29 of their papers we have counts for
29 papers
GeoWeaver: Accurate Long-Sequence 3D Reconstruction via Hierarchical Geometric Assembly
Tinghao Jiang, Sheng Tang, Shengzhe Wei +4
Long-sequence 3D reconstruction from RGB videos requires both accurate local geometry and globally consistent camera motion. Feed-forward models provide strong depth and pose predi…
UniQuery4R: Unified 4D Scene Reconstruction from a Single Query
Tiancheng Chen, Sheng Tang, Wenhua Jin +4
Reconstructing dynamic 4D scenes requires jointly estimating correspondence, geometry, object motion, and camera motion. Existing feed-forward methods typically predict dense task-…
City-Level 3D Surface Reconstruction with Viewpoint Orientation Partitioning and Scene Completion
Liang Han, Wenyuan Zhang, Junsheng Zhou +2
Multi-view 3D surface reconstruction is a longstanding challenge in computer vision. Although recent large-scale reconstruction methods based on 3D Gaussian Splatting (3DGS) achiev…
Sparse-View Surface Reconstruction using Gaussian Splatting through High-Confidence Depth Propagation with Normal Priors
Liang Han, Bangcai Wei, Junsheng Zhou +2
3D reconstruction from sparse views is a challenging task in 3D computer vision. Recent studies on 3D Gaussian Splatting (3DGS) have achieved remarkable results with sparse views i…
VidSplat: Gaussian Splatting Reconstruction with Geometry-Guided Video Diffusion Priors
Jimin Tang, Wenyuan Zhang, Junsheng Zhou +5
Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent eff…
GaussianGrow: Geometry-aware Gaussian Growing from 3D Point Clouds with Text Guidance
Weiqi Zhang, Junsheng Zhou, Haotian Geng +4
3D Gaussian Splatting has demonstrated superior performance in rendering efficiency and quality, yet the generation of 3D Gaussians still remains a challenge without proper geometr…
4C4D: 4 Camera 4D Gaussian Splatting
Junsheng Zhou, Zhifan Yang, Liang Han +4
This paper tackles the challenge of recovering 4D dynamic scenes from videos captured by as few as four portable cameras. Learning to model scene dynamics for temporally consistent…
AnchoredDream: Zero-Shot 360° Indoor Scene Generation from a Single View via Geometric Grounding
Runmao Yao, Junsheng Zhou, Zhen Dong +1
Single-view indoor scene generation plays a crucial role in a range of real-world applications. However, generating a complete 360° scene from a single image remains a highly ill-p…
U-CAN: Unsupervised Point Cloud Denoising with Consistency-Aware Noise2Noise Matching
Junsheng Zhou, Xingyu Shi, Haichuan Song +3
Point clouds captured by scanning sensors are often perturbed by noise, which have a highly negative impact on downstream tasks (e.g. surface reconstruction and shape understanding…
GAP: Gaussianize Any Point Clouds with Text Guidance
Weiqi Zhang, Junsheng Zhou, Haotian Geng +2
3D Gaussian Splatting (3DGS) has demonstrated its advantages in achieving fast and high-quality rendering. As point clouds serve as a widely-used and easily accessible form of 3D r…
iDiT-HOI: Inpainting-based Hand Object Interaction Reenactment via Video Diffusion Transformer
Zhelun Shen, Chenming Wu, Junsheng Zhou +7
Digital human video generation is gaining traction in fields like education and e-commerce, driven by advancements in head-body animation and lip-syncing technologies. However, rea…
NeRFPrior: Learning Neural Radiance Field as a Prior for Indoor Scene Reconstruction
Wenyuan Zhang, Emily Yue-ting Jia, Junsheng Zhou +4
Recently, it has shown that priors are vital for neural implicit functions to reconstruct high-quality surfaces from multi-view RGB images. However, current priors require large-sc…
Learning Bijective Surface Parameterization for Inferring Signed Distance Functions from Sparse Point Clouds with Grid Deformation
Takeshi Noda, Chao Chen, Junsheng Zhou +3
Inferring signed distance functions (SDFs) from sparse point clouds remains a challenge in surface reconstruction. The key lies in the lack of detailed geometric information in spa…
DiffGS: Functional Gaussian Splatting Diffusion
Junsheng Zhou, Weiqi Zhang, Yu-Shen Liu
3D Gaussian Splatting (3DGS) has shown convincing performance in rendering speed and fidelity, yet the generation of Gaussian Splatting remains a challenge due to its discreteness…
Binocular-Guided 3D Gaussian Splatting with View Consistency for Sparse View Synthesis
Liang Han, Junsheng Zhou, Yu-Shen Liu +1
Novel view synthesis from sparse inputs is a vital yet challenging task in 3D computer vision. Previous methods explore 3D Gaussian Splatting with neural priors (e.g. depth priors)…
Zero-Shot Scene Reconstruction from Single Images with Deep Prior Assembly
Junsheng Zhou, Yu-Shen Liu, Zhizhong Han
Large language and vision models have been leading a revolution in visual computing. By greatly scaling up sizes of data and model parameters, the large models learn deep priors wh…
Fast Learning of Signed Distance Functions from Noisy Point Clouds via Noise to Noise Mapping
Junsheng Zhou, Baorui Ma, Yu-Shen Liu +1
Learning signed distance functions (SDFs) from point clouds is an important task in 3D computer vision. However, without ground truth signed distances, point normals or clean point…
UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion
Junsheng Zhou, Weiqi Zhang, Baorui Ma +3
Diffusion models have shown remarkable results for image generation, editing and inpainting. Recent works explore diffusion models for 3D shape generation with neural implicit func…
Learning Continuous Implicit Field with Local Distance Indicator for Arbitrary-Scale Point Cloud Upsampling
Shujuan Li, Junsheng Zhou, Baorui Ma +2
Point cloud upsampling aims to generate dense and uniformly distributed point sets from a sparse point cloud, which plays a critical role in 3D computer vision. Previous methods ty…
NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views
Han Huang, Yulun Wu, Junsheng Zhou +3
Recently, neural implicit functions have demonstrated remarkable results in the field of multi-view reconstruction. However, most existing methods are tailored for dense views and…
Differentiable Registration of Images and LiDAR Point Clouds with VoxelPoint-to-Pixel Matching
Junsheng Zhou, Baorui Ma, Wenyuan Zhang +3
Cross-modality registration between 2D images from cameras and 3D point clouds from LiDARs is a crucial task in computer vision and robotic. Previous methods estimate 2D-3D corresp…
GeoDream: Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation
Baorui Ma, Haoge Deng, Junsheng Zhou +3
Text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models has shown great promise but still suffers from inconsistent 3D geometric structures (Janus…
Uni3D: Exploring Unified 3D Representation at Scale
Junsheng Zhou, Jinsheng Wang, Baorui Ma +3
Scaling up representations for images or text has been extensively investigated in the past few years and has led to revolutions in learning vision and language. However, scalable…
Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection
Junsheng Zhou, Baorui Ma, Shujuan Li +2
Latest methods represent shapes with open surfaces using unsigned distance functions (UDFs). They train neural networks to learn UDFs and reconstruct surfaces with the gradients ar…