49 citations · 174 across the 38 of their papers we have counts for
10 papers · 1 filter
VacuumVLA: Boosting VLA Capabilities via a Unified Suction and Gripping Tool for Complex Robotic Manipulation
Hui Zhou, Siyuan Huang, Minxing Li +3
Vision Language Action models have significantly advanced general purpose robotic manipulation by harnessing large scale pretrained vision and language representations. Among exist…
MCOP: Multi-UAV Collaborative Occupancy Prediction
Zefu Lin, Wenbo Chen, Xiaojuan Jin +5
Unmanned Aerial Vehicle (UAV) swarm systems necessitate efficient collaborative perception mechanisms for diverse operational scenarios. Current Bird's Eye View (BEV)-based approac…
EmbodiedCoder: Parameterized Embodied Mobile Manipulation via Modern Coding Model
Zefu Lin, Rongxu Cui, Chen Hanning +8
Recent advances in control robot methods, from end-to-end vision-language-action frameworks to modular systems with predefined primitives, have advanced robots' ability to follow n…
DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving
Yingyan Li, Shuyao Shang, Weisong Liu +10
Scaling Vision-Language-Action (VLA) models on large-scale data offers a promising path to achieving a more generalized driving intelligence. However, VLA models are limited by a `…
TC-Light: Temporally Coherent Generative Rendering for Realistic World Transfer
Yang Liu, Chuanchen Luo, Zimo Tang +6
Illumination and texture editing are critical dimensions for world-to-world transfer, which is valuable for applications including sim2real and real2real visual data scaling up for…
UI-Genie: A Self-Improving Approach for Iteratively Boosting MLLM-based Mobile GUI Agents
Han Xiao, Guozhi Wang, Yuxiang Chai +12
In this paper, we introduce UI-Genie, a self-improving framework addressing two key challenges in GUI agents: verification of trajectory outcome is challenging and high-quality tra…
End-to-End Driving with Online Trajectory Evaluation via BEV World Model
Yingyan Li, Yuqi Wang, Yang Liu +3
End-to-end autonomous driving has achieved remarkable progress by integrating perception, prediction, and planning into a fully differentiable framework. Yet, to fully realize its…
Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision
Xiaofeng Han, Shunpeng Chen, Zenghuang Fu +9
Robot vision has greatly benefited from advancements in multimodal fusion techniques and vision-language models (VLMs). We adopt a task-oriented perspective to systematically revie…
FlexDrive: Toward Trajectory Flexibility in Driving Scene Reconstruction and Rendering
Jingqiu Zhou, Lue Fan, Linjiang Huang +4
Driving scene reconstruction and rendering have advanced significantly using the 3D Gaussian Splatting. However, most prior research has focused on the rendering quality along a pr…
LayerAnimate: Layer-level Control for Animation
Yuxue Yang, Lue Fan, Zuzeng Lin +2
Traditional animation production decomposes visual elements into discrete layers to enable independent processing for sketching, refining, coloring, and in-betweening. Existing ani…