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20242026
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cs.CV2026

Spark3R: Asymmetric Token Reduction Makes Fast Feed-Forward 3D Reconstruction

Zecheng Tang, Jiaye Fu, Qiankun Gao +5

Feed-forward 3D reconstruction models based on Vision Transformers can directly estimate scene geometry and camera poses from a small set of input images, but scaling them to video…

cs.CV2025

Drive Any Mesh: 4D Latent Diffusion for Mesh Deformation from Video

Yahao Shi, Yang Liu, Yanmin Wu +4

We propose DriveAnyMesh, a method for driving mesh guided by monocular video. Current 4D generation techniques encounter challenges with modern rendering engines. Implicit methods…

cs.CV2025

InstanceGaussian: Appearance-Semantic Joint Gaussian Representation for 3D Instance-Level Perception

Haijie Li, Yanmin Wu, Jiarui Meng +4

3D scene understanding has become an essential area of research with applications in autonomous driving, robotics, and augmented reality. Recently, 3D Gaussian Splatting (3DGS) has…

cs.CV2025

SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography

Xuanyu Zhang, Jiarui Meng, Zhipei Xu +4

3D Gaussian Splatting (3DGS) has emerged as a premier method for 3D representation due to its real-time rendering and high-quality outputs, underscoring the critical need to protec…

cs.CV2024

RelayGS: Reconstructing Dynamic Scenes with Large-Scale and Complex Motions via Relay Gaussians

Qiankun Gao, Yanmin Wu, Chengxiang Wen +5

Reconstructing dynamic scenes with large-scale and complex motions remains a significant challenge. Recent techniques like Neural Radiance Fields and 3D Gaussian Splatting (3DGS) h…

cs.CV2024

Hybrid Fourier Score Distillation for Efficient One Image to 3D Object Generation

Shuzhou Yang, Yu Wang, Haijie Li +4

Single image-to-3D generation is pivotal for crafting controllable 3D assets. Given its under-constrained nature, we attempt to leverage 3D geometric priors from a novel view diffu…