1 citations · 1 across the 3 of their papers we have counts for
8 papers
Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation
Kailing Li, Tianwen Qian, Lijin Yang +4
Vision-Language Navigation (VLN) enables embodied agents to reach target locations in unseen environments by following language instructions. Despite recent progress with vision-la…
ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation
Liang Heng, Haoran Geng, Kaifeng Zhang +2
Dexterous manipulation is a cornerstone capability for robotic systems aiming to interact with the physical world in a human-like manner. Although vision-based methods have advance…
ToG-Bench: Task-Oriented Spatio-Temporal Grounding in Egocentric Videos
Qi'ao Xu, Tianwen Qian, Yuqian Fu +5
A core capability towards general embodied intelligence lies in localizing task-relevant objects from an egocentric perspective, formulated as Spatio-Temporal Video Grounding (STVG…
Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception
Lai Wei, Liangbo He, Jun Lan +9
Multimodal Large Language Models (MLLMs) excel at broad visual understanding but still struggle with fine-grained perception, where decisive evidence is small and easily overwhelme…
LLMs-guided adaptive compensator: Bringing Adaptivity to Automatic Control Systems with Large Language Models
Zhongchao Zhou, Yuxi Lu, Yaonan Zhu +5
With rapid advances in code generation, reasoning, and problem-solving, Large Language Models (LLMs) are increasingly applied in robotics. Most existing work focuses on high-level…
CrayonRobo: Object-Centric Prompt-Driven Vision-Language-Action Model for Robotic Manipulation
Xiaoqi Li, Lingyun Xu, Mingxu Zhang +8
In robotic, task goals can be conveyed through various modalities, such as language, goal images, and goal videos. However, natural language can be ambiguous, while images or video…