6 papers
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…
IRIS-SLAM: Unified Geo-Instance Representations for Robust Semantic Localization and Mapping
Tingyang Xiao, Liu Liu, Wei Feng +6
Geometry foundation models have significantly advanced dense geometric SLAM, yet existing systems often lack deep semantic understanding and robust loop closure capabilities. Meanw…
LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding
Hao Li, Minghan Qin, Zhengyu Zou +6
Applying Gaussian Splatting to perception tasks for 3D scene understanding is becoming increasingly popular. Most existing works primarily focus on rendering 2D feature maps from n…
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…
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…