43 citations · 68 across the 12 of their papers we have counts for
12 papers
CRAG: Can 3D Generative Models Help 3D Assembly?
Zeyu Jiang, Sihang Li, Siqi Tan +8
Most existing 3D assembly methods treat the problem as pure pose estimation, rearranging observed parts via rigid transformations. In contrast, human assembly naturally couples str…
From Intention to Execution: Probing the Generalization Boundaries of Vision-Language-Action Models
Irving Fang, Juexiao Zhang, Shengbang Tong +1
One promise that Vision-Language-Action (VLA) models hold over traditional imitation learning for robotics is to leverage the broad generalization capabilities of large Vision-Lang…
Co-VisiON: Co-Visibility ReasONing on Sparse Image Sets of Indoor Scenes
Chao Chen, Nobel Dang, Juexiao Zhang +7
Humans exhibit a remarkable ability to recognize co-visibility-the 3D regions simultaneously visible in multiple images-even when these images are sparsely distributed across a com…
When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis
Ruixuan Zhang, Beichen Wang, Juexiao Zhang +3
The increasing availability of traffic videos functioning on a 24/7/365 time scale has the great potential of increasing the spatio-temporal coverage of traffic accidents, which wi…
Multiview Scene Graph
Juexiao Zhang, Gao Zhu, Sihang Li +4
A proper scene representation is central to the pursuit of spatial intelligence where agents can robustly reconstruct and efficiently understand 3D scenes. A scene representation i…
CityWalker: Learning Embodied Urban Navigation from Web-Scale Videos
Xinhao Liu, Jintong Li, Yicheng Jiang +6
Navigating dynamic urban environments presents significant challenges for embodied agents, requiring advanced spatial reasoning and adherence to common-sense norms. Despite progres…
VLM See, Robot Do: Human Demo Video to Robot Action Plan via Vision Language Model
Beichen Wang, Juexiao Zhang, Shuwen Dong +2
Vision Language Models (VLMs) have recently been adopted in robotics for their capability in common sense reasoning and generalizability. Existing work has applied VLMs to generate…
Tell Me Where You Are: Multimodal LLMs Meet Place Recognition
Zonglin Lyu, Juexiao Zhang, Mingxuan Lu +2
Large language models (LLMs) exhibit a variety of promising capabilities in robotics, including long-horizon planning and commonsense reasoning. However, their performance in place…
LUWA Dataset: Learning Lithic Use-Wear Analysis on Microscopic Images
Jing Zhang, Irving Fang, Juexiao Zhang +7
Lithic Use-Wear Analysis (LUWA) using microscopic images is an underexplored vision-for-science research area. It seeks to distinguish the worked material, which is critical for un…
ActFormer: Scalable Collaborative Perception via Active Queries
Suozhi Huang, Juexiao Zhang, Yiming Li +1
Collaborative perception leverages rich visual observations from multiple robots to extend a single robot's perception ability beyond its field of view. Many prior works receive me…
URLOST: Unsupervised Representation Learning without Stationarity or Topology
Zeyu Yun, Juexiao Zhang, Yann LeCun +1
Unsupervised representation learning has seen tremendous progress. However, it is constrained by its reliance on domain specific stationarity and topology, a limitation not found i…
Word Embedding Visualization Via Dictionary Learning
Juexiao Zhang, Yubei Chen, Brian Cheung +1
Co-occurrence statistics based word embedding techniques have proved to be very useful in extracting the semantic and syntactic representation of words as low dimensional continuou…