8 citations · 20 across the 8 of their papers we have counts for
8 papers
3D FlowMatch Actor: Unified 3D Policy for Single- and Dual-Arm Manipulation
Nikolaos Gkanatsios, Jiahe Xu, Matthew Bronars +3
We present 3D FlowMatch Actor (3DFA), a 3D policy architecture for robot manipulation that combines flow matching for trajectory prediction with 3D pretrained visual scene represen…
3D Diffuser Actor: Policy Diffusion with 3D Scene Representations
Tsung-Wei Ke, Nikolaos Gkanatsios, Katerina Fragkiadaki
Diffusion policies are conditional diffusion models that learn robot action distributions conditioned on the robot and environment state. They have recently shown to outperform bot…
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Following
Brian Yang, Huangyuan Su, Nikolaos Gkanatsios +4
Diffusion models excel at modeling complex and multimodal trajectory distributions for decision-making and control. Reward-gradient guided denoising has been recently proposed to g…
ODIN: A Single Model for 2D and 3D Segmentation
Ayush Jain, Pushkal Katara, Nikolaos Gkanatsios +5
State-of-the-art models on contemporary 3D segmentation benchmarks like ScanNet consume and label dataset-provided 3D point clouds, obtained through post processing of sensed multi…
Act3D: 3D Feature Field Transformers for Multi-Task Robotic Manipulation
Theophile Gervet, Zhou Xian, Nikolaos Gkanatsios +1
3D perceptual representations are well suited for robot manipulation as they easily encode occlusions and simplify spatial reasoning. Many manipulation tasks require high spatial p…
Analogy-Forming Transformers for Few-Shot 3D Parsing
Nikolaos Gkanatsios, Mayank Singh, Zhaoyuan Fang +2
We present Analogical Networks, a model that encodes domain knowledge explicitly, in a collection of structured labelled 3D scenes, in addition to implicitly, as model parameters,…
Energy-based Models are Zero-Shot Planners for Compositional Scene Rearrangement
Nikolaos Gkanatsios, Ayush Jain, Zhou Xian +3
Language is compositional; an instruction can express multiple relation constraints to hold among objects in a scene that a robot is tasked to rearrange. Our focus in this work is…
Bottom Up Top Down Detection Transformers for Language Grounding in Images and Point Clouds
Ayush Jain, Nikolaos Gkanatsios, Ishita Mediratta +1
Most models tasked to ground referential utterances in 2D and 3D scenes learn to select the referred object from a pool of object proposals provided by a pre-trained detector. This…