most citedDust to Tower: Coarse-to-Fine Photo-Realistic Scene Reconstruction from Sparse Uncalibrated Images

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cs.CV2025

Mem4D: Decoupling Static and Dynamic Memory for Dynamic Scene Reconstruction

Xudong Cai, Shuo Wang, Peng Wang +7

Reconstructing dense geometry for dynamic scenes from a monocular video is a critical yet challenging task. Recent memory-based methods enable efficient online reconstruction, but…

cs.CV2025

MonoDream: Monocular Vision-Language Navigation with Panoramic Dreaming

Shuo Wang, Yongcai Wang, Zhaoxin Fan +8

Vision-Language Navigation (VLN) tasks often leverage panoramic RGB and depth inputs to provide rich spatial cues for action planning, but these sensors can be costly or less acces…

cs.CV2025

CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection

Zhe Huang, Shuo Wang, Yongcai Wang +1

Collaborative 3D object detection holds significant importance in the field of autonomous driving, as it greatly enhances the perception capabilities of each individual agent by fa…

cs.CV20241 cited

Dust to Tower: Coarse-to-Fine Photo-Realistic Scene Reconstruction from Sparse Uncalibrated Images

Xudong Cai, Yongcai Wang, Zhaoxin Fan +7

Photo-realistic scene reconstruction from sparse-view, uncalibrated images is highly required in practice. Although some successes have been made, existing methods are either Spars…

cs.CV2024

MambaVO: Deep Visual Odometry Based on Sequential Matching Refinement and Training Smoothing

Shuo Wang, Wanting Li, Yongcai Wang +5

Deep visual odometry has demonstrated great advancements by learning-to-optimize technology. This approach heavily relies on the visual matching across frames. However, ambiguous m…

cs.CV2024

GSLAMOT: A Tracklet and Query Graph-based Simultaneous Locating, Mapping, and Multiple Object Tracking System

Shuo Wang, Yongcai Wang, Zhimin Xu +5

For interacting with mobile objects in unfamiliar environments, simultaneously locating, mapping, and tracking the 3D poses of multiple objects are crucially required. This paper p…