60 citations · 76 across the 21 of their papers we have counts for
24 papers · 1 filter
LiteReality-Agent: An Agentic System for Interactable 3D Indoor Scene Reconstruction
Zhening Huang, Yueyan Li, Johnathan Chiu +5
We present LiteReality-Agent, an agentic system for reconstructing real indoor environments as realistic, articulated, and simulation-ready 3D scenes from RGB-D scans. At its core,…
LiFR v2: Completion-Augmented Event Propagation for High-Rate Dense Prediction
Tao Wan, Xiaoshan Wu, Yifei Yu +6
High-rate dense perception in dynamic environments is limited by the low update rate of RGB cameras, as rapid scene changes can occur between frames. Event cameras offer temporally…
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…
OptiGeo: Efficient Monocular Geometry for Embodied Perception in Optically Challenging Scenes
Muxin Liu, Tianbo Liu, Jing Xia +7
Monocular depth estimation has achieved strong open-domain generalization, yet reliable robotic deployment remains difficult in transparent, reflective, and specular environments,…
FoundationGeo: Learning Spatial Pixel-Wise Fields for Monocular Metric Geometry
Muxin Liu, Xiaoyang Lyu, Tianhe Ren +7
We present FoundationGeo, a two-stage framework that explicitly bridges relative and metric prediction via spatial calibration and principled data design. Stage 1 learns a high-fid…
Geometry-Instructed Video Editing
Chirui Chang, Xiaoyang Lyu, Yi-Hua Huang +7
Object-level geometric edits, including translating, rotating, scaling, duplicating, or removing an object, are routine operations in digital content creation (DCC) workflows, yet…
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…
Articraft: An Agentic System for Scalable Articulated 3D Asset Generation
Matt Zhou, Ruining Li, Xiaoyang Lyu +6
A bottleneck in learning to understand articulated 3D objects is the lack of large and diverse datasets. In this paper, we propose to leverage large language models (LLMs) to close…
LiFR-Seg: Anytime High-Frame-Rate Segmentation via Event-Guided Propagation
Xiaoshan Wu, Xiaoyang Lyu, Yifei Yu +3
Dense semantic segmentation in dynamic environments is fundamentally limited by the low-frame-rate (LFR) nature of standard cameras, which creates critical perceptual gaps between…
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…
EAG3R: Event-Augmented 3D Geometry Estimation for Dynamic and Extreme-Lighting Scenes
Xiaoshan Wu, Yifei Yu, Xiaoyang Lyu +5
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…
UniSplat: Unified Spatio-Temporal Fusion via 3D Latent Scaffolds for Dynamic Driving Scene Reconstruction
Chen Shi, Shaoshuai Shi, Xiaoyang Lyu +4
Feed-forward 3D reconstruction for autonomous driving has advanced rapidly, yet existing methods struggle with the joint challenges of sparse, non-overlapping camera views and comp…
DiST-4D: Disentangled Spatiotemporal Diffusion with Metric Depth for 4D Driving Scene Generation
Jiazhe Guo, Yikang Ding, Xiwu Chen +8
Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-sce…
MuDG: Taming Multi-modal Diffusion with Gaussian Splatting for Urban Scene Reconstruction
Yingshuang Zou, Yikang Ding, Chuanrui Zhang +6
Recent breakthroughs in radiance fields have significantly advanced 3D scene reconstruction and novel view synthesis (NVS) in autonomous driving. Nevertheless, critical limitations…
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…
How Far are AI-generated Videos from Simulating the 3D Visual World: A Learned 3D Evaluation Approach
Chirui Chang, Jiahui Liu, Zhengzhe Liu +6
Recent advancements in video diffusion models enable the generation of photorealistic videos with impressive 3D consistency and temporal coherence. However, the extent to which the…
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…
EscherNet: A Generative Model for Scalable View Synthesis
Xin Kong, Shikun Liu, Xiaoyang Lyu +3
We introduce EscherNet, a multi-view conditioned diffusion model for view synthesis. EscherNet learns implicit and generative 3D representations coupled with a specialised camera p…
DO3D: Self-supervised Learning of Decomposed Object-aware 3D Motion and Depth from Monocular Videos
Xiuzhe Wu, Xiaoyang Lyu, Qihao Huang +4
Although considerable advancements have been attained in self-supervised depth estimation from monocular videos, most existing methods often treat all objects in a video as static…
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…
Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video
Xiuzhe Wu, Pengfei Hu, Yang Wu +6
Synthesizing realistic videos according to a given speech is still an open challenge. Previous works have been plagued by issues such as inaccurate lip shape generation and poor im…