activity
20242026
collaborators

12 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence

Yalun Dai, Hao Li, Shulin Tian +10

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…