45 citations · 69 across the 14 of their papers we have counts for
11 papers · 1 filter
Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model
Liming Lu, Xianzheng Ma, Wenkun He +14
Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical principles. Existing approac…
Grounded 3D-Aware Spatial Vision-Language Modeling
An-Chieh Cheng, Yang Fu, Yatai Ji +12
We present GR3D, a spatial vision language model equipped with three complementary grounding capabilities--explicit 2D grounding, implicit 2D grounding, and monocular 3D grounding-…
EGM: Efficient Visual Grounding Language Models
Guanqi Zhan, Changye Li, Zhijian Liu +4
Visual grounding is an essential capability of Visual Language Models (VLMs) to understand the real physical world. Previous state-of-the-art grounding visual language models usual…
Inferring Dynamic Physical Properties from Video Foundation Models
Guanqi Zhan, Xianzheng Ma, Weidi Xie +1
We study the task of predicting dynamic physical properties from videos. More specifically, we consider physical properties that require temporal information to be inferred: elasti…
ELIP: Enhanced Visual-Language Foundation Models for Image Retrieval
Guanqi Zhan, Yuanpei Liu, Kai Han +2
The objective in this paper is to improve the performance of text-to-image retrieval. To this end, we introduce a new framework that can boost the performance of large-scale pre-tr…
Amodal Ground Truth and Completion in the Wild
Guanqi Zhan, Chuanxia Zheng, Weidi Xie +1
This paper studies amodal image segmentation: predicting entire object segmentation masks including both visible and invisible (occluded) parts. In previous work, the amodal segmen…
A General Protocol to Probe Large Vision Models for 3D Physical Understanding
Guanqi Zhan, Chuanxia Zheng, Weidi Xie +1
Our objective in this paper is to probe large vision models to determine to what extent they 'understand' different physical properties of the 3D scene depicted in an image. To thi…
Score-PA: Score-based 3D Part Assembly
Junfeng Cheng, Mingdong Wu, Ruiyuan Zhang +3
Autonomous 3D part assembly is a challenging task in the areas of robotics and 3D computer vision. This task aims to assemble individual components into a complete shape without re…
A Tri-Layer Plugin to Improve Occluded Detection
Guanqi Zhan, Weidi Xie, Andrew Zisserman
Detecting occluded objects still remains a challenge for state-of-the-art object detectors. The objective of this work is to improve the detection for such objects, and thereby imp…
Generative 3D Part Assembly via Dynamic Graph Learning
Jialei Huang, Guanqi Zhan, Qingnan Fan +5
Autonomous part assembly is a challenging yet crucial task in 3D computer vision and robotics. Analogous to buying an IKEA furniture, given a set of 3D parts that can assemble a si…
DLGAN: Disentangling Label-Specific Fine-Grained Features for Image Manipulation
Guanqi Zhan, Yihao Zhao, Bingchan Zhao +3
Recent studies have shown how disentangling images into content and feature spaces can provide controllable image translation/ manipulation. In this paper, we propose a framework t…