60 citations · 72 across the 13 of their papers we have counts for
13 papers
Mira-Scene: Pixel-Aligned Layouts for Generative 3D Scene Reconstruction
Yang-Tian Sun, Tianjia Liu, Zehuan Huang +7
Single-image 3D object generation can now produce high-fidelity assets, yet accurately placing them into a coherent scene layout remains an open challenge. A central difficulty lie…
Monocular Depth Estimation from a Single Image: Progress and Opportunities
Muxin Liu, Xiaoyang Lyu, Yang-Tian Sun +4
Monocular depth estimation has long stood as a fundamental challenge in computer vision, enabling a wide range of applications including 3D reconstruction, robotics, autonomous dri…
Dynamic Important Example Mining for Reinforcement Finetuning
Haoru Tan, Sitong Wu, Yanfeng Chen +9
Reinforcement fine-tuning (RFT) is increasingly used to strengthen the reasoning abilities of large models, yet its effectiveness is bound by how training data are selected and use…
Dataset Distillation by Influence Matching
Haoru Tan, Wang Wang, Sitong Wu +5
We revisit dataset distillation from an outcome-centric perspective. Rather than aligning process surrogates (per-step gradients or training trajectories), Influence Matching (Inf-…
Stabilizing Streaming Video Geometry via Dynamic Feature Normalization
Xiaoyang Lyu, Muxin Liu, Xiaoshan Wu +5
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 mod…
VideoSSM: Autoregressive Long Video Generation with Hybrid State-Space Memory
Yifei Yu, Xiaoshan Wu, Xinting Hu +8
Autoregressive (AR) diffusion enables streaming, interactive long-video generation by producing frames causally, yet maintaining coherence over minute-scale horizons remains challe…
UniGeo: Taming Video Diffusion for Unified Consistent Geometry Estimation
Yang-Tian Sun, Xin Yu, Zehuan Huang +5
Recently, methods leveraging diffusion model priors to assist monocular geometric estimation (e.g., depth and normal) have gained significant attention due to their strong generali…
Deformable Radial Kernel Splatting
Yi-Hua Huang, Ming-Xian Lin, Yang-Tian Sun +4
Recently, Gaussian splatting has emerged as a robust technique for representing 3D scenes, enabling real-time rasterization and high-fidelity rendering. However, Gaussians' inheren…
Splatter a Video: Video Gaussian Representation for Versatile Processing
Yang-Tian Sun, Yi-Hua Huang, Lin Ma +3
Video representation is a long-standing problem that is crucial for various down-stream tasks, such as tracking,depth prediction,segmentation,view synthesis,and editing. However, c…
3DGSR: Implicit Surface Reconstruction with 3D Gaussian Splatting
Xiaoyang Lyu, Yang-Tian Sun, Yi-Hua Huang +5
In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate 3D reconstruction with intricate detai…
Total-Decom: Decomposed 3D Scene Reconstruction with Minimal Interaction
Xiaoyang Lyu, Chirui Chang, Peng Dai +2
Scene reconstruction from multi-view images is a fundamental problem in computer vision and graphics. Recent neural implicit surface reconstruction methods have achieved high-quali…
Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting
Ziyi Yang, Xinyu Gao, Yangtian Sun +6
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-th…
SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes
Yi-Hua Huang, Yang-Tian Sun, Ziyi Yang +3
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…