activity
20232026
most citedAutonomous Driving in Unstructured Environments: How Far Have We Come?

6 citations · 11 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CV2026

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction

Tianbao Zhang, Zhenyu Liang, Zhenbo Song +7

High-resolution geometric prediction is essential for robust perception in autonomous driving, robotics, and AR/MR, but current foundation models are fundamentally limited by their…

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.CL2025

VerifyBench: Benchmarking Reference-based Reward Systems for Large Language Models

Yuchen Yan, Jin Jiang, Zhenbang Ren +9

Large reasoning models such as OpenAI o1 and DeepSeek-R1 have demonstrated remarkable performance in complex reasoning tasks. A critical component of their training is the incorpor…

cs.RO2025

Aux-Think: Exploring Reasoning Strategies for Data-Efficient Vision-Language Navigation

Shuo Wang, Yongcai Wang, Wanting Li +7

Vision-Language Navigation (VLN) is a critical task for developing embodied agents that can follow natural language instructions to navigate in complex real-world environments. Rec…

cs.CV2024★ 1 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.RO2024★ 6 cited

Autonomous Driving in Unstructured Environments: How Far Have We Come?

Chen Min, Shubin Si, Xu Wang +14

Research on autonomous driving in unstructured outdoor environments is less advanced than in structured urban settings due to challenges like environmental diversities and scene co…

cs.CV2024

VSFormer: Mining Correlations in Flexible View Set for Multi-view 3D Shape Understanding

Hongyu Sun, Yongcai Wang, Peng Wang +3

View-based methods have demonstrated promising performance in 3D shape understanding. However, they tend to make strong assumptions about the relations between views or learn the m…

cs.CV2024★ 3 cited

PRISM: PRogressive dependency maxImization for Scale-invariant image Matching

Xudong Cai, Yongcai Wang, Lun Luo +5

Image matching aims at identifying corresponding points between a pair of images. Currently, detector-free methods have shown impressive performance in challenging scenarios, thank…

cs.CV2024

VOLoc: Visual Place Recognition by Querying Compressed Lidar Map

Xudong Cai, Yongcai Wang, Zhe Huang +2

The availability of city-scale Lidar maps enables the potential of city-scale place recognition using mobile cameras. However, the city-scale Lidar maps generally need to be compre…

cs.CV2023★ 1 cited

ViewFormer: View Set Attention for Multi-view 3D Shape Understanding

Hongyu Sun, Yongcai Wang, Peng Wang +2

This paper presents ViewFormer, a simple yet effective model for multi-view 3d shape recognition and retrieval. We systematically investigate the existing methods for aggregating m…

cs.CV2023

ViPFormer: Efficient Vision-and-Pointcloud Transformer for Unsupervised Pointcloud Understanding

Hongyu Sun, Yongcai Wang, Xudong Cai +2

Recently, a growing number of work design unsupervised paradigms for point cloud processing to alleviate the limitation of expensive manual annotation and poor transferability of s…