2 citations · 4 across the 9 of their papers we have counts for
10 papers
Xiaomi-Robotics-1: Scaling Vision-Language-Action Models with over 100K Hours of Real-World Trajectories
Xiaomi Robotics Team, Jun Guo, Piaopiao Jin +31
We present Xiaomi-Robotics-1, a foundational vision-language-action (VLA) model capable of (1) following diverse language instructions to perform a wide range of mobile manipulatio…
AdaReP:Adaptive Re-Planning under Model Mismatch for Neural World-Model Predictive Control
Yutian Cheng, Xiaojian Ma, Xianhao Wang +6
Neural world models coupled with model predictive control (MPC) replan at every environment step to bound accumulated prediction error, but this incurs substantial computational ov…
Seeing Through Fog: Towards Fog-Invariant Action Recognition
Enqi Liu, Liyuan Pan, Zhi Gao +2
Foggy conditions are commonly encountered in real-world applications; however, existing action recognition approaches typically assume favorable weather and high-quality video inpu…
DEVIS-GRPO: Unleashing GRPO on Dynamic Extreme View Synthesis
Yi Zuo, Huimin Wu, Lingling Li +3
Trajectory-controlled video generation has become essential for controllable video generation. While current methods perform well under small-view camera motions, they degrade sign…
From Objects to Anywhere: A Holistic Benchmark for Multi-level Visual Grounding in 3D Scenes
Tianxu Wang, Zhuofan Zhang, Ziyu Zhu +5
3D visual grounding has made notable progress in localizing objects within complex 3D scenes. However, grounding referring expressions beyond objects in 3D scenes remains unexplore…
FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulation
Jun Guo, Xiaojian Ma, Yikai Wang +3
This paper investigates training better visual world models for robot manipulation, i.e., models that can predict future visual observations by conditioning on past frames and robo…
Embodied VideoAgent: Persistent Memory from Egocentric Videos and Embodied Sensors Enables Dynamic Scene Understanding
Yue Fan, Xiaojian Ma, Rongpeng Su +4
This paper investigates the problem of understanding dynamic 3D scenes from egocentric observations, a key challenge in robotics and embodied AI. Unlike prior studies that explored…
LongViTU: Instruction Tuning for Long-Form Video Understanding
Rujie Wu, Xiaojian Ma, Hai Ci +5
This paper introduces LongViTU, a large-scale (~121k QA pairs, ~900h videos), automatically generated dataset for long-form video understanding. We propose a systematic approach th…
Semantic Gaussians: Open-Vocabulary Scene Understanding with 3D Gaussian Splatting
Jun Guo, Xiaojian Ma, Yue Fan +2
Open-vocabulary 3D scene understanding presents a significant challenge in computer vision, with wide-ranging applications in embodied agents and augmented reality systems. Existin…
VideoAgent: A Memory-augmented Multimodal Agent for Video Understanding
Yue Fan, Xiaojian Ma, Rujie Wu +4
We explore how reconciling several foundation models (large language models and vision-language models) with a novel unified memory mechanism could tackle the challenging video und…