activity
20242026
most citedLightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregation

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

GeoQuery: Geometry-Query Diffusion for Sparse-View Reconstruction

Xiao Cao, Yuze Li, Youmin Zhang +4

3D Gaussian Splatting (3DGS) has emerged as a prominent paradigm for 3D reconstruction and novel view synthesis. However, it remains vulnerable to severe artifacts when trained und…

cs.CV2025

StereoCarla: A High-Fidelity Driving Dataset for Generalizable Stereo

Xianda Guo, Chenming Zhang, Ruilin Wang +6

Stereo matching plays a crucial role in enabling depth perception for autonomous driving and robotics. While recent years have witnessed remarkable progress in stereo matching algo…

cs.CV2024

Stereo Anything: Unifying Zero-shot Stereo Matching with Large-Scale Mixed Data

Xianda Guo, Chenming Zhang, Youmin Zhang +8

Stereo matching serves as a cornerstone in 3D vision, aiming to establish pixel-wise correspondences between stereo image pairs for depth recovery. Despite remarkable progress driv…

cs.CV2024★ 3 cited

LightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregation

Xianda Guo, Chenming Zhang, Youmin Zhang +4

We present LightStereo, a cutting-edge stereo-matching network crafted to accelerate the matching process. Departing from conventional methodologies that rely on aggregating comput…

cs.CV2024★ 1 cited

Learning Temporally Consistent Video Depth from Video Diffusion Priors

Jiahao Shao, Yuanbo Yang, Hongyu Zhou +6

This work addresses the challenge of streamed video depth estimation, which expects not only per-frame accuracy but, more importantly, cross-frame consistency. We argue that sharin…