17 citations · 27 across the 25 of their papers we have counts for
27 papers
PXDepth: Pixel-Space Modeling for Structure Preserving Monocular Depth Estimation
Zhiyuan Yuan, Guanying Chen, Lingteng Qiu +3
Recent monocular depth estimators achieve strong zero-shot generalization, yet often struggle to preserve fine-grained structures and object boundaries. We attribute this limitatio…
SpatialCrafter: Single Image World Modeling with Generative 3D Proxies
Chuan Fang, Lingteng Qiu, Yixun Liang +8
Explorable image-to-scene generation is essential for applications in gaming, robotics, and virtual reality. Existing methods based on video diffusion model (VDM) commonly rely on…
Glob3R: Global Structure-from-Motion with 3D Foundation Models
Junyuan Deng, Heng Li, Kejie Qiu +7
Recent 3D geometric foundation models, such as VGGT, provide robust feed-forward 3D reconstruction by directly predicting camera poses and 3D scene points from input images. Howeve…
PointSplat: Compact Gaussian Splatting via Human-Centric Prediction
Yujie Guo, Yudong Jin, Lingteng Qiu +7
Producing 3D human representations from input views on the fly is essential for immersive live streaming systems, where representation compactness is as critical as high fidelity g…
Large Depth Completion Model from Sparse Observations
Zhu Yu, Zhengyi Zhao, Runmin Zhang +7
This work presents the Large Depth Completion Model (LDCM), a simple, effective, and robust framework for single-view metric depth estimation with sparse observations. Without rely…
Towards Consistent Video Geometry Estimation
Zhu Yu, Jingnan Gao, Runmin Zhang +9
This work presents ViGeo, a feed-forward foundation model for recovering spatially dense and temporally consistent geometry from video sequences. Built upon a plain transformer arc…
PartNerFace: Part-based Neural Radiance Fields for Animatable Facial Avatar Reconstruction
Xianggang Yu, Lingteng Qiu, Xiaohang Ren +4
We present PartNerFace, a part-based neural radiance fields approach, for reconstructing animatable facial avatar from monocular RGB videos. Existing solutions either simply condit…
Condition Matters in Full-head 3D GANs
Heyuan Li, Huimin Zhang, Yuda Qiu +10
Conditioning is crucial for stable training of full-head 3D GANs. Without any conditioning signal, the model suffers from severe mode collapse, making it impractical to training. H…
ViSA: 3D-Aware Video Shading for Real-Time Upper-Body Avatar Creation
Fan Yang, Heyuan Li, Peihao Li +9
Generating high-fidelity upper-body 3D avatars from one-shot input image remains a significant challenge. Current 3D avatar generation methods, which rely on large reconstruction m…
HyPlaneHead: Rethinking Tri-plane-like Representations in Full-Head Image Synthesis
Heyuan Li, Kenkun Liu, Lingteng Qiu +4
Tri-plane-like representations have been widely adopted in 3D-aware GANs for head image synthesis and other 3D object/scene modeling tasks due to their efficiency. However, queryin…
LHM++: An Efficient Large Human Reconstruction Model for Pose-free Images to 3D
Lingteng Qiu, Peihao Li, Heyuan Li +9
Reconstructing animatable 3D humans from casually captured images of articulated subjects without camera or pose information is highly practical but remains challenging due to view…
LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds
Lingteng Qiu, Xiaodong Gu, Peihao Li +8
Animatable 3D human reconstruction from a single image is a challenging problem due to the ambiguity in decoupling geometry, appearance, and deformation. Recent advances in 3D huma…
MCMat: Multiview-Consistent and Physically Accurate PBR Material Generation
Shenhao Zhu, Lingteng Qiu, Xiaodong Gu +11
Existing 2D methods utilize UNet-based diffusion models to generate multi-view physically-based rendering (PBR) maps but struggle with multi-view inconsistency, while some 3D metho…
AniGS: Animatable Gaussian Avatar from a Single Image with Inconsistent Gaussian Reconstruction
Lingteng Qiu, Shenhao Zhu, Qi Zuo +9
Generating animatable human avatars from a single image is essential for various digital human modeling applications. Existing 3D reconstruction methods often struggle to capture f…
MVImgNet2.0: A Larger-scale Dataset of Multi-view Images
Xiaoguang Han, Yushuang Wu, Luyue Shi +7
MVImgNet is a large-scale dataset that contains multi-view images of ~220k real-world objects in 238 classes. As a counterpart of ImageNet, it introduces 3D visual signals via mult…
LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning
Zhe Li, Weihao Yuan, Yisheng He +7
Language plays a vital role in the realm of human motion. Existing methods have largely depended on CLIP text embeddings for motion generation, yet they fall short in effectively a…
DreamDissector: Learning Disentangled Text-to-3D Generation from 2D Diffusion Priors
Zizheng Yan, Jiapeng Zhou, Fanpeng Meng +6
Text-to-3D generation has recently seen significant progress. To enhance its practicality in real-world applications, it is crucial to generate multiple independent objects with in…
StableNormal: Reducing Diffusion Variance for Stable and Sharp Normal
Chongjie Ye, Lingteng Qiu, Xiaodong Gu +6
This work addresses the challenge of high-quality surface normal estimation from monocular colored inputs (i.e., images and videos), a field which has recently been revolutionized…
IPoD: Implicit Field Learning with Point Diffusion for Generalizable 3D Object Reconstruction from Single RGB-D Images
Yushuang Wu, Luyue Shi, Junhao Cai +6
Generalizable 3D object reconstruction from single-view RGB-D images remains a challenging task, particularly with real-world data. Current state-of-the-art methods develop Transfo…
VideoMV: Consistent Multi-View Generation Based on Large Video Generative Model
Qi Zuo, Xiaodong Gu, Lingteng Qiu +8
Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we…
RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D
Lingteng Qiu, Guanying Chen, Xiaodong Gu +7
Lifting 2D diffusion for 3D generation is a challenging problem due to the lack of geometric prior and the complex entanglement of materials and lighting in natural images. Existin…
MVHumanNet: A Large-scale Dataset of Multi-view Daily Dressing Human Captures
Zhangyang Xiong, Chenghong Li, Kenkun Liu +9
In this era, the success of large language models and text-to-image models can be attributed to the driving force of large-scale datasets. However, in the realm of 3D vision, while…
SAMPro3D: Locating SAM Prompts in 3D for Zero-Shot Instance Segmentation
Mutian Xu, Xingyilang Yin, Lingteng Qiu +3
We introduce SAMPro3D for zero-shot instance segmentation of 3D scenes. Given the 3D point cloud and multiple posed RGB-D frames of 3D scenes, our approach segments 3D instances by…
REC-MV: REconstructing 3D Dynamic Cloth from Monocular Videos
Lingteng Qiu, Guanying Chen, Jiapeng Zhou +3
Reconstructing dynamic 3D garment surfaces with open boundaries from monocular videos is an important problem as it provides a practical and low-cost solution for clothes digitizat…