3 citations · 9 across the 19 of their papers we have counts for
21 papers
S4VY: Segment Anything in Feed-Forward 4D Visual Geometry
Jingdong Zhang, Xin Li, Jan Kautz +2
Accurate instance segmentation in dynamic scenes is important for downstream applications such as robotics and autonomous driving. Existing Segment Anything models operate primaril…
NBS: No Bias Stereo
Vage Taamazyan, Zhuowen Shen, Stefan Hinterstoisser +6
Stereo reconstruction is one of the last remaining Computer Vision tasks where all state-of-the-art methods employ a heavy architectural inductive bias. Even though it has been dem…
MEC-Patch: Visible-Infrared Cross-Modal Adversarial Attack Driven by Intrinsic Material Emissivity Laws
Zhixiang Huang, Xinbo Nie, Wenxuan Wang +4
With the widespread deployment of visible-infrared multimodal perception systems in safety-critical domains such as autonomous driving, evaluating their cross-modal adversarial rob…
Beyond Thinking: Imagining in 360 for Humanoid Visual Search
Jingdong Zhang, Yizhou Wang, Zhengzhong Tu +3
Humanoid Visual Search (HVS) requires agents to actively explore immersive 360 environments. While prior methods treat this as a monolithic task relying on cumulative, mult…
DiffHDR: Re-Exposing LDR Videos with Video Diffusion Models
Zhengming Yu, Li Ma, Mingming He +11
Most digital videos are stored in 8-bit low dynamic range (LDR) formats, where much of the original high dynamic range (HDR) scene radiance is lost due to saturation and quantizati…
3DGS-HPC: Distractor-free 3D Gaussian Splatting with Hybrid Patch-wise Classification
Jiahao Chen, Yipeng Qin, Ganlong Zhao +3
3D Gaussian Splatting (3DGS) has demonstrated remarkable performance in novel view synthesis and 3D scene reconstruction, but its quality often degrades in real-world environments…
SPGen: Spherical Projection as Consistent and Flexible Representation for Single Image 3D Shape Generation
Jingdong Zhang, Weikai Chen, Yuan Liu +6
Existing single-view 3D generative models typically adopt multiview diffusion priors to reconstruct object surfaces, yet they remain prone to inter-view inconsistencies and are una…
PDT: Point Distribution Transformation with Diffusion Models
Jionghao Wang, Cheng Lin, Yuan Liu +7
Point-based representations have consistently played a vital role in geometric data structures. Most point cloud learning and processing methods typically leverage the unordered an…
NeuVAS: Neural Implicit Surfaces for Variational Shape Modeling
Pengfei Wang, Qiujie Dong, Fangtian Liang +11
Neural implicit shape representation has drawn significant attention in recent years due to its smoothness, differentiability, and topological flexibility. However, directly modeli…
CrossGen: Learning and Generating Cross Fields for Quad Meshing
Qiujie Dong, Jiepeng Wang, Rui Xu +10
Cross fields play a critical role in various geometry processing tasks, especially for quad mesh generation. Existing methods for cross field generation often struggle to balance c…
3R-GS: Best Practice in Optimizing Camera Poses Along with 3DGS
Zhisheng Huang, Peng Wang, Jingdong Zhang +3
3D Gaussian Splatting (3DGS) has revolutionized neural rendering with its efficiency and quality, but like many novel view synthesis methods, it heavily depends on accurate camera…
CADDreamer: CAD Object Generation from Single-view Images
Yuan Li, Cheng Lin, Yuan Liu +6
Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand i…
Controllable 3D Outdoor Scene Generation via Scene Graphs
Yuheng Liu, Xinke Li, Yuning Zhang +6
Three-dimensional scene generation is crucial in computer vision, with applications spanning autonomous driving, gaming and the metaverse. Current methods either lack user control…
WonderHuman: Hallucinating Unseen Parts in Dynamic 3D Human Reconstruction
Zilong Wang, Zhiyang Dou, Yuan Liu +7
In this paper, we present WonderHuman to reconstruct dynamic human avatars from a monocular video for high-fidelity novel view synthesis. Previous dynamic human avatar reconstructi…
SolidGS: Consolidating Gaussian Surfel Splatting for Sparse-View Surface Reconstruction
Zhuowen Shen, Yuan Liu, Zhang Chen +9
Gaussian splatting has achieved impressive improvements for both novel-view synthesis and surface reconstruction from multi-view images. However, current methods still struggle to…
GausSurf: Geometry-Guided 3D Gaussian Splatting for Surface Reconstruction
Jiepeng Wang, Yuan Liu, Peng Wang +5
3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine det…
SVGS: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors
Rui Xu, Wenyue Chen, Jiepeng Wang +7
Gaussian Splatting demonstrates impressive results in multi-view reconstruction based on Gaussian explicit representations. However, the current Gaussian primitives only have a sin…
Multi-Task Label Discovery via Hierarchical Task Tokens for Partially Annotated Dense Predictions
Jingdong Zhang, Hanrong Ye, Xin Li +2
In recent years, simultaneous learning of multiple dense prediction tasks with partially annotated label data has emerged as an important research area. Previous works primarily fo…
Skull-to-Face: Anatomy-Guided 3D Facial Reconstruction and Editing
Yongqing Liang, Congyi Zhang, Junli Zhao +2
Deducing the 3D face from a skull is a challenging task in forensic science and archaeology. This paper proposes an end-to-end 3D face reconstruction pipeline and an exploration me…
Disentangled Clothed Avatar Generation from Text Descriptions
Jionghao Wang, Yuan Liu, Zhiyang Dou +7
In this paper, we introduce a novel text-to-avatar generation method that separately generates the human body and the clothes and allows high-quality animation on the generated ava…
Surf-D: Generating High-Quality Surfaces of Arbitrary Topologies Using Diffusion Models
Zhengming Yu, Zhiyang Dou, Xiaoxiao Long +9
We present Surf-D, a novel method for generating high-quality 3D shapes as Surfaces with arbitrary topologies using Diffusion models. Previous methods explored shape generation wit…