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Found 12 papers, 9 papers with code
ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
We introduce and open source ManiSkill3, the fastest state-visual GPU parallelized robotics simulator with contact-rich physics targeting generalizable manipulation.
Point-SAM: Promptable 3D Segmentation Model for Point Clouds
The development of 2D foundation models for image segmentation has been significantly advanced by the Segment Anything Model (SAM).
Part-Guided 3D RL for Sim2Real Articulated Object Manipulation
Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots.
Robo360: A 3D Omnispective Multi-Material Robotic Manipulation Dataset
Building robots that can automate labor-intensive tasks has long been the core motivation behind the advancements in computer vision and the robotics community.
FG-NeRF: Flow-GAN based Probabilistic Neural Radiance Field for Independence-Assumption-Free Uncertainty Estimation
Existing works rely on the independence assumption of points in the radiance field or the pixels in input views to obtain tractable forms of the probability density function.
NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Support
We present a method for generating high-quality watertight manifold meshes from multi-view input images.
ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
Generalizable manipulation skills, which can be composed to tackle long-horizon and complex daily chores, are one of the cornerstones of Embodied AI.
ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
Here we propose SAPIEN Manipulation Skill Benchmark (ManiSkill) to benchmark manipulation skills over diverse objects in a full-physics simulator.
O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning
Contrary to the vast literature in modeling, perceiving, and understanding agent-object (e. g., human-object, hand-object, robot-object) interaction in computer vision and robotics, very few past works have studied the task of object-object interaction, which also plays an important role in robotic manipulation and planning tasks.
MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo
We present MVSNeRF, a novel neural rendering approach that can efficiently reconstruct neural radiance fields for view synthesis.
NeuTex: Neural Texture Mapping for Volumetric Neural Rendering
We achieve this by introducing a 3D-to-2D texture mapping (or surface parameterization) network into volumetric representations.
SAPIEN: A SimulAted Part-based Interactive ENvironment
To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real robot is indispensable.
