1 citations · 1 across the 14 of their papers we have counts for
14 papers
S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence
Yalun Dai, Hao Li, Shulin Tian +8
Real-world spatial intelligence requires reasoning over a continuous and evolving 3D world, yet existing VLMs and tool-augmented agents largely remain tied to static, stateless inf…
IGGT4D: Streaming 4D Instance-Grounded Geometry Transformer
Zhengyu Zou, Hao Li, Kuixuan Jiao +7
Real-world spatial intelligence requires agents to understand scenes from continuous video streams, where objects move, persist, disappear, and reappear over time. While recent spa…
SpatialBench: Is Your Spatial Foundation Model an All-Round Player?
Haosong Peng, Hao Li, Jiaqi Chen +10
While spatial foundation models have demonstrated impressive performance on standard datasets, a critical question remains: are they truly all-round players capable of generalizing…
Holi-Spatial: Evolving Video Streams into Holistic 3D Spatial Intelligence
Yuanyuan Gao, Hao Li, Yifei Liu +14
The pursuit of spatial intelligence fundamentally relies on access to large-scale, fine-grained 3D data. However, existing approaches predominantly construct spatial understanding…
Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform
Yuning Gong, Yifei Liu, Yifan Zhan +21
Neural rendering, particularly 3D Gaussian Splatting (3DGS), has evolved rapidly and become a key component for building world models. However, existing viewer solutions remain fra…
VDNeRF: Vision-only Dynamic Neural Radiance Field for Urban Scenes
Zhengyu Zou, Jingfeng Li, Hao Li +5
Neural Radiance Fields (NeRFs) implicitly model continuous three-dimensional scenes using a set of images with known camera poses, enabling the rendering of photorealistic novel vi…
IGGT: Instance-Grounded Geometry Transformer for Semantic 3D Reconstruction
Hao Li, Zhengyu Zou, Fangfu Liu +8
Humans naturally perceive the geometric structure and semantic content of a 3D world as intertwined dimensions, enabling coherent and accurate understanding of complex scenes. Howe…
ExGS: Extreme 3D Gaussian Compression with Diffusion Priors
Jiaqi Chen, Xinhao Ji, Yuanyuan Gao +7
Neural scene representations, such as 3D Gaussian Splatting (3DGS), have enabled high-quality neural rendering; however, their large storage and transmission costs hinder deploymen…
Proxy-GS: Unified Occlusion Priors for Training and Inference in Structured 3D Gaussian Splatting
Yuanyuan Gao, Yuning Gong, Yifei Liu +6
3D Gaussian Splatting (3DGS) has emerged as an efficient approach for achieving photorealistic rendering. Recent MLP-based variants further improve visual fidelity but introduce su…
CityGS-X: A Scalable Architecture for Efficient and Geometrically Accurate Large-Scale Scene Reconstruction
Yuanyuan Gao, Hao Li, Jiaqi Chen +5
Despite its significant achievements in large-scale scene reconstruction, 3D Gaussian Splatting still faces substantial challenges, including slow processing, high computational co…
CoSurfGS:Collaborative 3D Surface Gaussian Splatting with Distributed Learning for Large Scene Reconstruction
Yuanyuan Gao, Yalun Dai, Hao Li +7
3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or…
DGTR: Distributed Gaussian Turbo-Reconstruction for Sparse-View Vast Scenes
Hao Li, Yuanyuan Gao, Haosong Peng +7
Novel-view synthesis (NVS) approaches play a critical role in vast scene reconstruction. However, these methods rely heavily on dense image inputs and prolonged training times, mak…
VDG: Vision-Only Dynamic Gaussian for Driving Simulation
Hao Li, Jingfeng Li, Dingwen Zhang +7
Dynamic Gaussian splatting has led to impressive scene reconstruction and image synthesis advances in novel views. Existing methods, however, heavily rely on pre-computed poses and…
XLD: A Cross-Lane Dataset for Benchmarking Novel Driving View Synthesis
Hao Li, Chenming Wu, Ming Yuan +7
Comprehensive testing of autonomous systems through simulation is essential to ensure the safety of autonomous driving vehicles. This requires the generation of safety-critical sce…