activity
20242026
most citedOmniBind: Large-scale Omni Multimodal Representation via Binding Spaces

1 citations · 1 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

SigLIP-HD by Fine-to-Coarse Supervision

Lihe Yang, Zhen Zhao, Hengshuang Zhao

High-quality visual representation is a long-standing pursuit in computer vision. In the context of multimodal LLMs (MLLMs), feeding higher-resolution images can produce more fine-…

cs.CV2026

WorldCompass: Reinforcement Learning for Long-Horizon World Models

Zehan Wang, Tengfei Wang, Haiyu Zhang +9

This work presents WorldCompass, a novel Reinforcement Learning (RL) post-training framework for the long-horizon, interactive video-based world models, enabling them to explore th…

cs.CV2026

Orient Anything V2: Unifying Orientation and Rotation Understanding

Zehan Wang, Ziang Zhang, Jiayang Xu +5

This work presents Orient Anything V2, an enhanced foundation model for unified understanding of object 3D orientation and rotation from single or paired images. Building upon Orie…

cs.CV2025

VLN-R1: Vision-Language Navigation via Reinforcement Fine-Tuning

Zhangyang Qi, Zhixiong Zhang, Yizhou Yu +2

Vision-Language Navigation (VLN) is a core challenge in embodied AI, requiring agents to navigate real-world environments using natural language instructions. Current language mode…

cs.CV2025

GenSpace: Benchmarking Spatially-Aware Image Generation

Zehan Wang, Jiayang Xu, Ziang Zhang +4

Humans can intuitively compose and arrange scenes in the 3D space for photography. However, can advanced AI image generators plan scenes with similar 3D spatial awareness when crea…

cs.CV2025

Depth Anything with Any Prior

Zehan Wang, Siyu Chen, Lihe Yang +4

This work presents Prior Depth Anything, a framework that combines incomplete but precise metric information in depth measurement with relative but complete geometric structures in…