10 papers
DEGround: An Effective Baseline for Ego-centric 3D Visual Grounding with a Homogeneous Framework
Yani Zhang, Dongming Wu, Hao Shi +3
A core task in embodied intelligence is ego-centric 3D visual grounding. Existing methods typically adopt two-stage, heterogeneous pipelines that pair a detector with a separate gr…
MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation
Hao Shi, Bin Xie, Yingfei Liu +7
Temporal context is essential for robotic manipulation because such tasks are inherently non-Markovian, yet mainstream VLA models typically overlook it and struggle with long-horiz…
SpatialActor: Exploring Disentangled Spatial Representations for Robust Robotic Manipulation
Hao Shi, Bin Xie, Yingfei Liu +5
Robotic manipulation requires precise spatial understanding to interact with objects in the real world. Point-based methods suffer from sparse sampling, leading to the loss of fine…
Dexbotic: Open-Source Vision-Language-Action Toolbox
Bin Xie, Erjin Zhou, Fan Jia +36
In this paper, we present Dexbotic, an open-source Vision-Language-Action (VLA) model toolbox based on PyTorch. It aims to provide a one-stop VLA research service for professionals…
GeoVLA: Empowering 3D Representations in Vision-Language-Action Models
Lin Sun, Bin Xie, Yingfei Liu +3
Vision-Language-Action (VLA) models have emerged as a promising approach for enabling robots to follow language instructions and predict corresponding actions. However, current VLA…
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping
Dongming Wu, Yanping Fu, Saike Huang +8
General robotic grasping systems require accurate object affordance perception in diverse open-world scenarios following human instructions. However, current studies suffer from th…