Highlights
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Lists (32)
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3D Vision
Tools and Algorithms for 3D dataAR/VR
Architecture
Classic Vision
Classic ideas, methods, algorithms for low-level vision tasks, and 2D applicationDepth Estimation
dexterous hand
Diffusion Models
Foundation Models, feature
Game AI
Gaussian Splatting
humanoid
Learn from Videos
LLM
LVM
Manipulation
MLLM
Mobile Manipulation
Neural Fields
Explore the theoretical foundations, implementations, and advancements in neural fields, with a particular emphasis on 3D scene synthesis and reconstructionPhysics Simulator
Point Cloud
Real-Robot
RL
Tools and Algorithms for Reinforcement Learning and RoboticsRobots
Simulation
SLAM
tactile sensing
Teleoperation
Tools
Useful Geek toolsvector-database
Visualization
VLA-RL
Voxel
Stars
Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
[CoRL 2025] ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training
Code for RSS 2025 paper "Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies"
Visual Imitation Enables Contextual Humanoid Control. arXiV, 2025.
[CoRL 2025] RISE-2: A Generalizable Imitation Learning Policy
[NeurIPS 2025, Spotlight] Rectified Point Flow: Generic Point Cloud Pose Estimation
[CVPR 2025] UniK3D: Universal Camera Monocular 3D Estimation
Universal Monocular Metric Depth Estimation
[NeurIPS 2025] Official implementation of "RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics"
Nvidia GEAR Lab's initiative to solve the robotics data problem using world models
NVIDIA Isaac GR00T N1.5 - A Foundation Model for Generalist Robots.
A curated list of state-of-the-art research in embodied AI, focusing on vision-language-action (VLA) models, vision-language navigation (VLN), and related multimodal learning approaches.
DexUMI: Using Human Hand as the Universal Manipulation Interface for Dexterous Manipulation
Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.
Attention mappers and visualisation for transformer-based Physical AI policies
[ICLR 25] Code for "Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning"
[ICRA 25] FLaRe: Achieving Masterful and Adaptive Robot Policies with Large-Scale Reinforcement Learning Fine-Tuning