most citedSeed1.5-VL Technical Report

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

eess.IV2025

Latent Space Consistency for Sparse-View CT Reconstruction

Duoyou Chen, Yunqing Chen, Can Zhang +3

Computed Tomography (CT) is a widely utilized imaging modality in clinical settings. Using densely acquired rotational X-ray arrays, CT can capture 3D spatial features. However, it…

cs.CV20251 cited

Seed1.5-VL Technical Report

Dong Guo, Faming Wu, Feida Zhu +194

We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…

cs.CV2025

IAAO: Interactive Affordance Learning for Articulated Objects in 3D Environments

Can Zhang, Gim Hee Lee

This work presents IAAO, a novel framework that builds an explicit 3D model for intelligent agents to gain understanding of articulated objects in their environment through interac…

cs.CV2025

econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians

Can Zhang, Gim Hee Lee

The primary focus of most recent works on open-vocabulary neural fields is extracting precise semantic features from the VLMs and then consolidating them efficiently into a multi-v…

cs.CV2025

CoSpace: Benchmarking Continuous Space Perception Ability for Vision-Language Models

Yiqi Zhu, Ziyue Wang, Can Zhang +2

Vision-Language Models (VLMs) have recently witnessed significant progress in visual comprehension. As the permitting length of image context grows, VLMs can now comprehend a broad…

cs.CV2024

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…