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Drive-HWM: Hierarchical World Models for Dynamic-Latent Guided Autonomous Driving
Zhaoxin Fan, Tianbao Zhang, Wenjun Wu +5
World models offer a promising paradigm for autonomous driving by predicting how traffic scenes may evolve and using such predictions to support action generation. However, existin…
LiteMVS: Efficient Multi-View Stereo with Foundation Distillation and Expert Aggregation
Tianbao Zhang, Zeyu Liu, Shuyu Wu +4
Real-time 3D perception is crucial for robotics, augmented reality, and embodied intelligence applications. Existing multi-view stereo (MVS) methods primarily rely on geometric cor…
STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching
Hao Wang, Haoran Geng, Xiaotong Yang +7
Stereo matching is a fundamental task in 3D reconstruction. Despite remarkable advances, the prevailing paradigms formulate stereo matching as a deterministic regression problem, c…
MapDream: Task-Driven Map Learning for Vision-Language Navigation
Guoxin Lian, Shuo Wang, Yucheng Wang +7
Vision-Language Navigation (VLN) requires agents to follow natural language instructions in partially observed 3D environments, motivating map representations that aggregate spatia…