activity
20242026
most citedL-MAGIC: Language Model Assisted Generation of Images with Coherence

2 citations · 4 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV2026

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth

Yuecheng Liu, Junda Cheng, Longliang Liu +4

Video depth estimation extends monocular prediction into the temporal domain to ensure coherence. However, existing methods often suffer from spatial blurring in fine-detail region…

cs.CV2026

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…

cs.CV2025

PriOr-Flow: Enhancing Primitive Panoramic Optical Flow with Orthogonal View

Longliang Liu, Miaojie Feng, Junda Cheng +3

Panoramic optical flow enables a comprehensive understanding of temporal dynamics across wide fields of view. However, severe distortions caused by sphere-to-plane projections, suc…

cs.CV2025

A Wavelet-based Stereo Matching Framework for Solving Frequency Convergence Inconsistency

Xiaobao Wei, Jiawei Liu, Dongbo Yang +3

We find that the EPE evaluation metrics of RAFT-stereo converge inconsistently in the low and high frequency regions, resulting high frequency degradation (e.g., edges and thin obj…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025★ 1 cited

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…

cs.CV2024★ 1 cited

Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry

Zhaoxing Zhang, Junda Cheng, Gangwei Xu +3

Recent approaches to VO have significantly improved performance by using deep networks to predict optical flow between video frames. However, existing methods still suffer from noi…

cs.CV2024

RoMeO: Robust Metric Visual Odometry

Junda Cheng, Zhipeng Cai, Zhaoxing Zhang +4

Visual odometry (VO) aims to estimate camera poses from visual inputs -- a fundamental building block for many applications such as VR/AR and robotics. This work focuses on monocul…

cs.CV2024★ 2 cited

L-MAGIC: Language Model Assisted Generation of Images with Coherence

Zhipeng Cai, Matthias Mueller, Reiner Birkl +6

In the current era of generative AI breakthroughs, generating panoramic scenes from a single input image remains a key challenge. Most existing methods use diffusion-based iterativ…