5 papers
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-…
SCOPE: Scale-Consistent One-Pass Estimation of 3D Geometry
Zheng Zhang, Lihe Yang, Tianyu Yang +6
We present SCOPE (Scale-Consistent One-Pass Estimation of 3D Geometry), a novel approach for estimating 3D geometry from extended monocular video sequences, where existing methods…
In Pursuit of Pixel Supervision for Visual Pre-training
Lihe Yang, Shang-Wen Li, Yang Li +5
At the most basic level, pixels are the source of the visual information through which we perceive the world. Pixels contain information at all levels, ranging from low-level attri…
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…
UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation
Lihe Yang, Zhen Zhao, Hengshuang Zhao
Semi-supervised semantic segmentation (SSS) aims at learning rich visual knowledge from cheap unlabeled images to enhance semantic segmentation capability. Among recent works, UniM…