5 citations · 12 across the 25 of their papers we have counts for
9 papers · 1 filter
MMSI-Video-Bench: A Holistic Benchmark for Video-Based Spatial Intelligence
Jingli Lin, Runsen Xu, Shaohao Zhu +11
Spatial understanding over continuous visual input is crucial for MLLMs to evolve into general-purpose assistants in physical environments. Yet there is still no comprehensive benc…
ChangingGrounding: 3D Visual Grounding in Changing Scenes
Miao Hu, Zhiwei Huang, Tai Wang +4
Real-world robots localize objects from natural-language instructions while scenes around them keep changing. Yet most of the existing 3D visual grounding (3DVG) method still assum…
VFlowOpt: A Token Pruning Framework for LMMs with Visual Information Flow-Guided Optimization
Sihan Yang, Runsen Xu, Chenhang Cui +3
Large Multimodal Models (LMMs) excel in visual-language tasks by leveraging numerous visual tokens for fine-grained visual information, but this token redundancy results in signifi…
CronusVLA: Towards Efficient and Robust Manipulation via Multi-Frame Vision-Language-Action Modeling
Hao Li, Shuai Yang, Yilun Chen +8
Recent vision-language-action (VLA) models built on pretrained vision-language models (VLMs) have demonstrated strong performance in robotic manipulation. However, these models rem…
Learning Video Generation for Robotic Manipulation with Collaborative Trajectory Control
Xiao Fu, Xintao Wang, Xian Liu +5
Recent advances in video diffusion models shows promise for generating robotic decision-making data, with trajectory conditions further enabling fine-grained control. However, exis…
MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence
Sihan Yang, Runsen Xu, Yiman Xie +10
Spatial intelligence is essential for multimodal large language models (MLLMs) operating in the complex physical world. Existing benchmarks, however, probe only single-image relati…
Multi-SpatialMLLM: Multi-Frame Spatial Understanding with Multi-Modal Large Language Models
Runsen Xu, Weiyao Wang, Hao Tang +5
Multi-modal large language models (MLLMs) have rapidly advanced in visual tasks, yet their spatial understanding remains limited to single images, leaving them ill-suited for physi…
Novel Demonstration Generation with Gaussian Splatting Enables Robust One-Shot Manipulation
Sizhe Yang, Wenye Yu, Jia Zeng +5
Visuomotor policies learned from teleoperated demonstrations face challenges such as lengthy data collection, high costs, and limited data diversity. Existing approaches address th…
HOMIE: Humanoid Loco-Manipulation with Isomorphic Exoskeleton Cockpit
Qingwei Ben, Feiyu Jia, Jia Zeng +3
Generalizable humanoid loco-manipulation poses significant challenges, requiring coordinated whole-body control and precise, contact-rich object manipulation. To address this, this…