44 citations · 44 across the 12 of their papers we have counts for
17 papers · 1 filter
EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic Segmentation
Mingkui Tan, Zhuangwei Zhuang, Sitao Chen +4
We study multi-sensor fusion for 3D semantic segmentation that is important to scene understanding for many applications, such as autonomous driving and robotics. Existing fusion-b…
DexWorldModel: Causal Latent World Modeling towards Automated Learning of Embodied Tasks
Yueci Deng, Guiliang Liu, Kui Jia
Deploying generative World-Action Models for manipulation is severely bottlenecked by redundant pixel-level reconstruction, memory scaling, and sequential inferenc…
PAct: Part-Decomposed Single-View Articulated Object Generation
Qingming Liu, Xinyue Yao, Shuyuan Zhang +4
Articulated objects are central to interactive 3D applications, including embodied AI, robotics, and VR/AR, where functional part decomposition and kinematic motion are essential.…
Towards Human-Level 3D Relative Pose Estimation: Generalizable, Training-Free, with Single Reference
Yuan Gao, Yajing Luo, Junhong Wang +2
Humans can easily deduce the relative pose of a previously unseen object, without labeling or training, given only a single query-reference image pair. This is arguably achieved by…
PicoPose: Progressive Pixel-to-Pixel Correspondence Learning for Novel Object Pose Estimation
Lihua Liu, Jiehong Lin, Zhenxin Liu +1
RGB-based novel object pose estimation is critical for rapid deployment in robotic applications, yet zero-shot generalization remains a key challenge. In this paper, we introduce P…
Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition
Longkun Zou, Kangjun Liu, Ke Chen +3
Learning semantic representations from point sets of 3D object shapes is often challenged by significant geometric variations, primarily due to differences in data acquisition meth…