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RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation
Developing robust and general-purpose robotic manipulation policies is a key goal in the field of robotics.
Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulation
Based on the mapping, Lift3D utilizes the 2D foundation model to directly encode point cloud data, leveraging large-scale pretrained knowledge to construct explicit 3D robotic representations while minimizing spatial information loss.
CrowdMoGen: Zero-Shot Text-Driven Collective Motion Generation
Crowd Motion Generation is essential in entertainment industries such as animation and games as well as in strategic fields like urban simulation and planning.
Ranked #1 on
Motion Generation
on KIL-ML
Large Motion Model for Unified Multi-Modal Motion Generation
In this work, we present Large Motion Model (LMM), a motion-centric, multi-modal framework that unifies mainstream motion generation tasks into a generalist model.
Mask-Guided Image Person Removal with Data Synthesis
As a special case of common object removal, image person removal is playing an increasingly important role in social media and criminal investigation domains.
Estimation of causal effects of multiple treatments in healthcare database studies with rare outcomes
The preponderance of large-scale healthcare databases provide abundant opportunities for comparative effectiveness research.
Predict Future Sales using Ensembled Random Forests
This is a method report for the Kaggle data competition 'Predict future sales'.
