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Yi-Hua Huang

9 accepted papers

2026

ObjectMorpher: 3D-Aware Image Editing via Deformable 3DGS

CVPR 2026

Achieving precise, object-level control in image editing remains challenging: 2D methods lack 3D awareness and often yield ambiguous or implausible results, while existing 3D-aware approaches rely on heavy optimization or incomplete monocular reconstructions. We present ObjectMorpher, a unified, int

Cited by 0SourceScholar
2026

Stabilizing Streaming Video Geometry via Dynamic Feature Normalization

CVPR 2026

Consistent 3D geometry estimation from streaming RGB input is crucial for real-world applications such as autonomous driving, embodied AI, and large-scale reconstruction. While modern monocular geometry foundation models achieve strong single-image accuracy, they exhibit severe temporal inconsistenc

Cited by 0SourcecodeScholar
2025

Deformable Radial Kernel Splatting

CVPR 2025poster

Recently, Gaussian splatting has emerged as a robust technique for representing 3D scenes, enabling real-time rasterization and high-fidelity rendering. However, Gaussians' inherent radial symmetry and smoothness constraints limit their ability to represent complex shapes, often requiring thousands…

Cited by 1SourcePDFScholar
2025

EAG3R: Event-Augmented 3D Geometry Estimation for Dynamic and Extreme-Lighting Scenes

NeurIPS 2025spotlight

Robust 3D geometry estimation from videos is critical for applications such as autonomous navigation, SLAM, and 3D scene reconstruction. Recent methods like DUSt3R demonstrate that regressing dense pointmaps from image pairs enables accurate and efficient pose-free reconstruction. However, existing…

Cited by 0SourceScholar
2025

How Far are AI-generated Videos from Simulating the 3D Visual World: A Learned 3D Evaluation Approach

ICCV 2025poster

Recent advancements in video diffusion models enable the generation of photorealistic videos with impressive 3D consistency and temporal coherence. However, the extent to which these AI-generated videos simulate the 3D visual world remains underexplored. In this paper, we introduce Learned 3D Evalua…

Cited by 0SourcePDFScholar
2024

SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes

CVPR 2024poster

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel view synthesis. Building upon this technique we propose a new r…

2024

Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting

NeurIPS 2024poster

The recent advancements in 3D Gaussian splatting (3D-GS) have not only facilitated real-time rendering through modern GPU rasterization pipelines but have also attained state-of-the-art rendering quality. Nevertheless, despite its exceptional rendering quality and performance on standard datasets, 3…

Cited by 45SourcePDFScholar
2024

Splatter a Video: Video Gaussian Representation for Versatile Processing

NeurIPS 2024poster

Video representation is a long-standing problem that is crucial for various downstream tasks, such as tracking, depth prediction, segmentation, view synthesis, and editing. However, current methods either struggle to model complex motions due to the absence of 3D structure or rely on implicit 3D rep…

Cited by 7SourcePDFScholar
2022

StylizedNeRF: Consistent 3D Scene Stylization As Stylized NeRF via 2D-3D Mutual Learning

CVPR 2022poster

3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered from different views. Directly applying methods for image or video stylization to 3D scenes cannot achieve such consistenc…

Cited by 172PDFcodeScholar