1 citations · 1 across the 8 of their papers we have counts for
9 papers
RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation
Haoyu Zhao, Xingyue Zhao, Hangyu Li +6
Scaling robot learning requires massive, diverse trajectory data, yet collection is currently bottlenecked by physical teleoperation, where every demonstration binds operator time…
RynnWorld-4D: 4D Embodied World Models for Robotic Manipulation
Haoyu Zhao, Xingyue Zhao, Siteng Huang +3
Robotic manipulation in the open world requires not only recognizing what a scene looks like, but also anticipating how its 3D structure moves under interaction. We argue that sync…
Articulat3D: Reconstructing Articulated Digital Twins From Monocular Videos with Geometric and Motion Constraints
Lijun Guo, Haoyu Zhao, Xingyue Zhao +5
Building high-fidelity digital twins of articulated objects from visual data remains a central challenge. Existing approaches depend on multi-view captures of the object in discret…
Control of Microrobots with Reinforcement Learning under On-Device Compute Constraints
Yichen Liu, Kesava Viswanadha, Zhongyu Li +2
An important function of autonomous microrobots is the ability to perform robust movement over terrain. This paper explores an edge ML approach to microrobot locomotion, allowing f…
Rank-Aware Agglomeration of Foundation Models for Immunohistochemistry Image Cell Counting
Zuqi Huang, Mengxin Tian, Huan Liu +6
Accurate cell counting in immunohistochemistry (IHC) images is critical for quantifying protein expression and aiding cancer diagnosis. However, the task remains challenging due to…
GenDexHand: Generative Simulation for Dexterous Hands
Feng Chen, Zhuxiu Xu, Tianzhe Chu +7
Data scarcity remains a fundamental bottleneck for embodied intelligence. Existing approaches use large language models (LLMs) to automate gripper-based simulation generation, but…
High-Fidelity Simulated Data Generation for Real-World Zero-Shot Robotic Manipulation Learning with Gaussian Splatting
Haoyu Zhao, Cheng Zeng, Linghao Zhuang +11
The scalability of robotic learning is fundamentally bottlenecked by the significant cost and labor of real-world data collection. While simulated data offers a scalable alternativ…
Lumina-Video: Efficient and Flexible Video Generation with Multi-scale Next-DiT
Dongyang Liu, Shicheng Li, Yutong Liu +16
Recent advancements have established Diffusion Transformers (DiTs) as a dominant framework in generative modeling. Building on this success, Lumina-Next achieves exceptional perfor…
IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image Models
Jiayi Lei, Renrui Zhang, Xiangfei Hu +12
With the rapid development of diffusion models, text-to-image(T2I) models have made significant progress, showcasing impressive abilities in prompt following and image generation.…