3 citations · 8 across the 13 of their papers we have counts for
15 papers
PointForward: Feedforward Driving Reconstruction through Point-Aligned Representations
Cheng Chi, Xianqi Wang, Hongcheng Luo +9
High-fidelity reconstruction of driving scenes is crucial for autonomous driving. While recent feedforward 3D Gaussian Splatting (3DGS) methods enable fast reconstruction, their pe…
PCSTracker: Long-Term Scene Flow Estimation for Point Cloud Sequences
Min Lin, Gangwei Xu, Xianqi Wang +2
Point cloud scene flow estimation is fundamental to long-term and fine-grained 3D motion analysis. However, existing methods are typically limited to pairwise settings and struggle…
PromptStereo: Zero-Shot Stereo Matching via Structure and Motion Prompts
Xianqi Wang, Hao Yang, Hangtian Wang +4
Modern stereo matching methods have leveraged monocular depth foundation models to achieve superior zero-shot generalization performance. However, most existing methods primarily f…
Generalized Geometry Encoding Volume for Real-time Stereo Matching
Jiaxin Liu, Gangwei Xu, Xianqi Wang +2
Real-time stereo matching methods primarily focus on enhancing in-domain performance but often overlook the critical importance of generalization in real-world applications. In con…
Pixel-Perfect Depth with Semantics-Prompted Diffusion Transformers
Gangwei Xu, Haotong Lin, Hongcheng Luo +11
This paper presents Pixel-Perfect Depth, a monocular depth estimation model based on pixel-space diffusion generation that produces high-quality, flying-pixel-free point clouds fro…
DEPTHOR++: Robust Depth Enhancement from a Real-World Lightweight dToF and RGB Guidance
Jijun Xiang, Longliang Liu, Xuan Zhu +3
Depth enhancement, which converts raw dToF signals into dense depth maps using RGB guidance, is crucial for improving depth perception in high-precision tasks such as 3D reconstruc…
DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB Image
Jijun Xiang, Xuan Zhu, Xianqi Wang +4
Depth enhancement, which uses RGB images as guidance to convert raw signals from dToF into high-precision, dense depth maps, is a critical task in computer vision. Although existin…
SVDC: Consistent Direct Time-of-Flight Video Depth Completion with Frequency Selective Fusion
Xuan Zhu, Jijun Xiang, Xianqi Wang +5
Lightweight direct Time-of-Flight (dToF) sensors are ideal for 3D sensing on mobile devices. However, due to the manufacturing constraints of compact devices and the inherent physi…
BANet: Bilateral Aggregation Network for Mobile Stereo Matching
Gangwei Xu, Jiaxin Liu, Xianqi Wang +5
State-of-the-art stereo matching methods typically use costly 3D convolutions to aggregate a full cost volume, but their computational demands make mobile deployment challenging. D…
ZeroStereo: Zero-shot Stereo Matching from Single Images
Xianqi Wang, Hao Yang, Gangwei Xu +6
State-of-the-art supervised stereo matching methods have achieved remarkable performance on various benchmarks. However, their generalization to real-world scenarios remains challe…
MonSter++: Unified Stereo Matching, Multi-view Stereo, and Real-time Stereo with Monodepth Priors
Junda Cheng, Wenjing Liao, Zhipeng Cai +10
We introduce MonSter++, a geometric foundation model for multi-view depth estimation, unifying rectified stereo matching and unrectified multi-view stereo. Both tasks fundamentally…
FlowMamba: Learning Point Cloud Scene Flow with Global Motion Propagation
Min Lin, Gangwei Xu, Yun Wang +2
Scene flow methods based on deep learning have achieved impressive performance. However, current top-performing methods still struggle with ill-posed regions, such as extensive fla…
IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching
Gangwei Xu, Xianqi Wang, Zhaoxing Zhang +3
Stereo matching is a core component in many computer vision and robotics systems. Despite significant advances over the last decade, handling matching ambiguities in ill-posed regi…
Selective-Stereo: Adaptive Frequency Information Selection for Stereo Matching
Xianqi Wang, Gangwei Xu, Hao Jia +1
Stereo matching methods based on iterative optimization, like RAFT-Stereo and IGEV-Stereo, have evolved into a cornerstone in the field of stereo matching. However, these methods s…
Iterative Geometry Encoding Volume for Stereo Matching
Gangwei Xu, Xianqi Wang, Xiaohuan Ding +1
Recurrent All-Pairs Field Transforms (RAFT) has shown great potentials in matching tasks. However, all-pairs correlations lack non-local geometry knowledge and have difficulties ta…